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Capitalizing On The Promise of AI

The rapid proliferation of Artificial Intelligence (AI) tools like ChatGPT have created both awe and anxiety among people, and led to intense debates about the future of humanity. How should people prepare for a world where AI has a significant presence? What does the future of work look like?

Business leaders have an equally enormous task ahead of them. What are the threats and opportunities posed by AI? What changes do they need to make to their strategy, operations or culture in order to stay relevant? And how does one handle this radical transformation of work while keeping employees engaged?

One estimate says that AI will unlock $15.7 trillion in productivity gains by 2030. However, companies have to take deliberate steps to adapt their organizations in order to capitalize on the potential that AI offers.   

With Productivity Commodified, Creativity Becomes More Salient

AI is enabling productivity gains that are orders of magnitude higher than what humans can accomplish. AI can spit out code snippets or new graphics in a matter of seconds, compared to hours it takes a person. 

Competing with AI on skills where it can outperform people is pointless. Any business that doesn’t adopt AI productivity and employs people to do the same tasks, will soon fail. Instead, the most promising approach is to harmoniously coexist with AI where people focus on tasks that are uniquely human, like creativity, while AI handles more routine tasks. 

Focusing on innovation is important from a differentiation perspective too. When everyone uses AI to help improve their productivity, productivity becomes commodified. The only way then, to stand out among your peers is by using creativity – finding new ways to use the latest technology or creating new capabilities that delight customers. As an example, the low-code/no-code platforms are allowing people from different industries, including health and finance, to create their own applications and improve their workflows. 

Creativity is where humans have a distinct advantage. AI hasn’t performed well when it comes to creative tasks because creativity, by definition, requires production of ideas that don’t exist before. Even though AI is transforming the creative industry, the nature of its output is only superficially creative. Current set of AI tools are only good at rearranging existing elements in different ways to give an illusion of creativity. When prompted to create something that is truly original, tools like ChatGPT tend to fail. 

Leaders need to recognize that human creativity is now the differentiator for their business and they need to invest heavily in fostering internal innovation. 

Laying Off People Is The Wrong Strategy

Staying ahead of the AI acceleration requires proactively redesigning the boundary between human and AI work. This is a continually shifting line and businesses have to be agile when it comes to rearranging work for maximum productivity and innovation. 

As a business leader, it might be tempting to think that with AI taking over more and more tasks, your company needs fewer people to do the work that was being done before. This mindset can be dangerous for a company’s competitive advantage because it does not tap into the productivity gains that any new disruptive technology like AI unleashes. Barring a few domains (like some service industries), for any industry that has scalability potential and demands continuous innovation, reducing overall headcount will slow progress and almost certainly backfire in the long run. 

To see why this approach is damaging in the long run, let’s assume that your work requires some level of innovation to stay competitive in your market and therefore needs humans-in-the-loop. As more work starts shifting towards AI, it seems reasonable to reduce headcount in order to retain the same level of productivity for a much smaller cost. 

However, after a certain level of reduction, people become the critical resource in an organization. Even assuming that people are only doing tasks related to creativity that AI doesn’t handle well,  the organization becomes limited by the level of innovation it can harness from its employee base. As the AI capability expands even more (at a much faster rate than people upskilling), the extra capacity remains untapped due to limited people resources. After a short-term boost in productivity and lower costs, organizations get hamstrung in their ability to produce outsized innovations that can put them ahead of their competitors. 

Instead of simply reducing headcount to maintain the current levels of productivity, leaders need to take a long-term approach to talent management. Retaining and hiring people with the right skill set for innovation will help organizations take advantage of growing AI capabilities and provide higher levels of productivity and innovation compared to their peers. 

Engineering A High Performance Culture

A natural consequence of the increased productivity offered by AI, is that it allows more complex work to be possible. Complex work is high on both innovation and productivity, and the more complex the work, the more you need to tap into the intelligence and expertise of others. However, handling complexity, when humans are a critical part of the loop, is tricky. Groups can behave as intelligent swarms but they can also arrive at incredibly poor outcomes. How smartly a group behaves depends on the overall ability of individuals in the group as well as how independently they are allowed to think. Relatively smart people when thinking without the influence of others, cancel out each other’s errors and biases leading to much better decision making and problem solving that wouldn’t be possible at an individual level.

The single most important thing that organizations can do, in addition to hiring good talent, is to set up processes, tools and norms that allow people to contribute ideas and participate in decision making in independent ways. Without the right performance-focused culture, organizations will find it hard to capitalize on the higher complexity demands. 

Leadership Takeaways

Any transformative technology, by its very definition, radically changes the way people do things and opens up new markets and opportunities. How companies respond to the new environment determines how well they can capitalize new opportunities. 

Compared to disruptive technologies of the past, AI places new challenges due to the rapid pace of development. Companies need an agile approach to managing people and work. 

  • Innovation Management is key: With high productivity gains that benefit everyone, It’s inevitable that people-work will shift towards creativity. How well companies harness employee innovation will determine how they differentiate in the market and tap into the value that AI provides.
  • Hire for the long-term: Automation eliminates some jobs but typically creates many more new ones. A Deloitte study found that automation in the UK created over 4x more jobs than it eliminated that on average paid more. Instead of laying off people in order to boost short-term efficiency metrics, companies should focus on retaining and retraining employees to handle the higher workloads that are bound to come. 
  • Build a culture of performance: With AI taking over time-consuming tasks, more complex work that involves higher innovation and productivity will now be possible. Complex problem solving relies on individuals with different expertise to work together towards a common goal. Leaders will need to create a high-performance culture that incentivizes both individual expertise and swarm intelligence. 
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Why Managing Innovation Is Key To Organizational Success

Analogies are tricky. They can suddenly illuminate a hidden facet and bring to light new insights, new ideas and new solutions. But just as often, they push you to think in a single direction, that when taken too far, causes more harm than good. 

One analogy that is surfacing again is that of wartime and peacetime CEOs. Now that many companies are facing existential crises, there are calls to move away from a peacetime mode and bring a more wartime mentality to doing business. But this is a false choice. Companies are not at war (yes, they have to compete but that’s different) or at peace – instead, their primary task is to continuously innovate and stay relevant. 

The reason that this particular analogy is dangerous is that a warlike approach – think of a general directing orders, employing (mostly) sticks and (sometimes) carrots to get his troops to perform – is the exact opposite of what is needed for true innovation to take place on a regular basis. To be fair, the analogy works at times because it has some truth to it. But every analogy has its limitations. A wartime approach works in narrow situations for short periods of time, but making it the default mode of operation in an environment where high levels of innovation are the only solution to stay alive can only cause long-term damage.

The Two Beasts: Innovation and Productivity

Every company has to do innovative work as well as routine or productive work. For example, deciding what new product or feature to release that is both novel and solves an important customer problem is innovative work. With the innovative idea finalized and the workability of the novel aspect determined, implementing it becomes more of a routine/productive work. Even though both kinds of work require problem solving (barring some of the most mundane routine tasks), they are of very different nature. While most people think of creativity as a fun, relaxing activity, in reality it is more cognitively demanding compared to critical or logical thinking.  

Productive work is much more linear and therefore predictable in nature, making it easier to plan and track. In contrast, innovative work is much more non-linear, it requires multiple iterations and carries larger risks. While project management tools can handle productive work well, innovation management needs a very different type of tool to capture its underlying risk and complexity. 

Incentives also work differently for the two kinds of work. External motivators (like monetary rewards or threat of layoffs) can improve performance of routine tasks but can backfire for creative work in some situations. When people are nudged to adopt an extrinsic orientation or expect to be rewarded for a task, they produce less creative work. 

And finally, even though both kinds of work require collaboration, the nature of collaboration is different. For routine/productive work, collaboration is primarily coordination of tasks – tracking individual tasks and dependencies between different tasks and people. Creative work, on the other hand, requires collaboration of ideas – different ideas clashing together to create something much more interesting. In other words, even the day to day work that people engage in, including the kinds of things people talk about in meetings, is vastly different for innovative and productive work. 

Innovative and productive work are both equally essential for a company. However, they are two very different beasts and the real challenge comes in managing both without compromising either. 

When productivity metrics are applied to innovative work, as often happens in the corporate environment, a natural and predictable consequence is for innovation levels to drop. If you are tasked with a feature and your success is tracked through completion deadlines, there really is no option for you other than to pick the safest and simplest implementation that allows you to show up “green” on the project dashboard. Risk averseness starts to creep in at every level from padding estimates to reducing complexity, and innovation, which by its very nature involves high risk, is suppressed. 

Or, when companies implement some form of “rank and yank” system, idea collaboration among employees drops. If you are forced to compete with the person sitting next to you, it doesn’t make sense for you to collaborate and share credit if you believe you have a winning idea. An idea that could have bloomed with new perspectives, remains stunted. People become more focused on protecting their turf, leading to more politics and again, less innovation. 

If you think that hiring the smartest people would circumvent this problem, you would be mistaken. The underlying currents of human motivation and self-preservation are far too strong for things to go any other way. Most people eventually learn to adapt to the system and those who can’t or don’t want to, get frustrated and leave. 

The challenge for any company is to manage both these processes successfully, and neither the wartime nor peacetime approach is adequate. 

How The Manhattan Project Managed Radical Innovation

One of the most interesting examples to have successfully tamed the two beasts to produce groundbreaking work was the Manhattan Project, which produced the first nuclear weapons. To understand how impressive this accomplishment was consider the following:  

  • The Manhattan project started modestly but grew to about 130,000 people in just a few  years, spread across multiple locations.
  • The team faced huge scientific and technical challenges – prior research on producing fissionable was very preliminary and had many gaps. Processes that were eventually adopted, either did not exist before the project or had never been used with radioactive materials before. 
  • Fears that the German nuclear research team would produce the first atomic bomb created a strong time pressure. Fundamental research, and the design and building of the plant had to be done concurrently, something that had never been done before. 

These and other issues placed considerable management stress from scaling the team to shipping a challenging product on an accelerated schedule. So, how did the Manhattan project pull off such a feat?

To start, Leslie Richard Groves, the general in charge of the overall project, had the foresight to recognize that the typical command-and-control management style would not yield the required levels of innovation and there was no existing playbook to go by. Despite being in the middle of an actual war, he took a decidedly “un-wartime” approach to management. He first hired J. Robert Oppenheimer, a well respected theoretical physicist at UC Berkeley, as his counterpart to work with the scientists and researchers. Effectively working as co-CEOs, they found new ways of managing people and work in order to accomplish their audacious goals. 

And they faced massive challenges from the get go. For example, when Groves asked scientists how much fissionable material would be needed for each bomb, he expected an estimate within 20%-50% and was horrified when he got a factor of ten! He quipped, “My position could well be compared with that of a caterer who is told he must be prepared to serve anywhere between ten and a thousand guests. But after extensive discussion of this point, I concluded that it simply was not possible then to arrive at a more precise answer.”

Faced with such high levels of uncertainties, Oppenheimer and Groves realized that they will have to pursue multiple solutions at the same time. Given the time constraint, they decided to explore all options in parallel both for producing fissionable material and for gun design. They spun off multiple teams to explore different alternatives, and plant design proceeded under the assumption that any or all of these approaches would be needed. As research progressed, Oppenheimer realized that some of the processes could be combined for higher efficiency, a lucky turn of events that wouldn’t have happened without the parallel approach! 

Managing Innovation

Groves and Oppenheimer showed that it is possible to create an environment where there is a balance between urgency and innovation, structure and flexibility, hierarchy and egalitarianism. 

Innovation is fundamentally about managing uncertainty and risk, and the more radical the innovation the higher the uncertainty to manage. Using a top-down, highly directive leadership style doesn’t work because it increases risk (one person’s judgment is more error prone for complex problems) and reduces intrinsic motivation among employees which is essential for innovative problem solving. 

Despite the fact that Groves and Oppenheimer were both highly competent in their own ways, they did not push down any directive that would interfere with problem solving. Instead they did the opposite – by really listening to the people doing the work, they were able to clearly understand the inherent limitations in the project. They did several other things that led to  a creative climate. For example, Oppenheimer insisted early on that scientists have full access to the compound so they could observe all aspects of the project, leading to free flow of ideas. He was also known to take good care of his people, so compensations were generous and equitable. Teams also didn’t shy away from conflicts – vigorous debates were common but they were focused on problem solving. Intentionally or intuitively, they made sure that none of the factors that harm creativity and problem solving were accidentally introduced in their management approach. By enabling the scientists and engineers, they allowed more creative solutions to emerge for the myriad of challenges that kept popping up.  

Groves and Oppenheimer were successful, not by following any pre-existing playbook, but by systematically removing any barriers that came in the way of innovation. 

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Address Unfinished Learning Using Creativity And Arts  

During the Covid-19 pandemic, students all over the world faced one of the largest disruptors of education in history. School closures across more than 190 countries impacted the routine and learning outcomes of 1.6 Billion students. By August 2020, 93% of households in the US reported the use of remote learning. Despite things returning to normal for over a year, we continue to see the ripple effect of this massive disruption. 

A number of organizations and researchers have tried to estimate the loss in learning due to the pandemic. A report by Stanford University estimated that during Spring 2020, students lost between 57 to 183 days of learning in Reading and from 136 to 232 days of learning in Math. A study in the Netherlands, which had a relatively lockdown period and is known for its equitable and well-funded schools, showed that students made little to no progress in learning from home. 

One of the challenges with the analyses on learning loss thus far, is that they focus narrowly on a few subjects, primarily math and reading. Finding an effective set of solutions to address unfinished learning is not an easy task. However, there is a wrong solution – solely relying on standardized tests. A myopic focus on test scores leads to sub-par teaching (“teaching to the test”) and pushes out more holistic interventions. We have seen this play out before when the No Child Left Behind Act was implemented in 2002. The Act converted testing as an informational mechanism to an accountability mechanism, changing teaching patterns inside classrooms. Teachers spent less time on subjects that were not being tested, like the arts, and spent less time on open-ended exploratory work like project based learning. 

What we need are more holistic approaches that build student enthusiasm, curiosity and engagement towards learning. Here are three strategies to incorporate when designing intervention programs to address unfinished learning, without falling into the trap of standardized testing. 

Teach For Creativity

Incorporating creative thinking into regular subjects, like math, reading or science, deepens learning. Paradoxically, this approach ends up improving standardized test scores despite test results not being an explicit goal. Creative thinking encourages students to think about a concept from multiple perspectives, question assumptions they might be making and synthesize solutions from multiple strands. These cognitive processes help students deepen their understanding of the subject matter and retain information for longer. More importantly, they help students become better thinkers and problem solvers in the long run. 

For teachers to incorporate creativity into the classroom, they need to be mindful of the distinction between “teaching creatively” and “teaching for creativity.” When educators find a clever way to introduce a concept in the classroom, say using Bitmoji classrooms, they are teaching creatively. Their own creativity is at play in designing the lesson plan for the concept. This by itself is a good thing if it makes the lesson more engaging and helps students learn the concept more easily. However, “teaching for creativity” goes a step further – it allows students to build and exercise their own creativity. 

Well designed project-based learning modules are one way to encourage students to be more creative. However, it’s not hard to incorporate creative thinking in smaller doses by substituting a couple of traditional assignment questions with more creative ones. With this approach neither the students or the teachers are burdened with extra work. Key elements to keep in mind when incorporating creativity, in big or small doses, are:

  • Open-ended problems where multiple solutions are valid.
  • Problems are designed so that one more creative cognitive processes, like associative or analogical thinking, are engaged. 
  • An ability to share their work with their peers and learn from them.  

Integrate Arts

High quality arts programs, especially visual arts and music, have a strong correlation with academic success. Arts provides an avenue for students to build confidence to try new things in a safe environment. Incorporating arts increases both children’s self-efficacy and original thinking, according to a research study. As the authors noted, “Self-efficacious children believe they can be agents in creating their own futures and are more optimistic about what the world has in store for them.”

A randomized controlled trial with over ten thousand K-12 students in Texas, found that arts-learning experiences led to fewer disciplinary issues, higher student engagement and improved writing achievements. 

Reevaluate Evaluations

While standardized tests are a useful way to track student progress, they should be a small part of broader evaluations. Teachers should balance graded work with non-graded work that rely on constructive feedback. Quantitative scores orient students away from their own intrinsic motivation to extrinsic motivation, which leads to higher anxiety and lower interest in the subject matter. Providing opportunities to students to share their projects or other original work with their peers and get their feedback is another low-pressure way for students to learn from each other. Finally, teachers should also encourage frequent self-evaluations to build student capacity to critically analyze their own work. When students find their own areas of improvement, they are much more intrinsically motivated to improve and learn. 

The learning loss created by the pandemic is significant and real, but we need to approach it cautiously. Prioritizing standardized test scores instead of more holistic approaches can lead to disastrous consequences in the long-term. Instead we need to double down on tried and tested methods – incorporating creative thinking and arts, and toning down the performance pressure.  

This article first appeared on edCircuit.

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3 Reasons Why Innovation Is The Best Organizational Strategy

As we start the new year, events and challenges from the last few years are continuing to shape our lives and the way we do business. Companies have had to make peace with remote/hybrid work being the new normal, adjust their cost structures to deal with economic uncertainties and redesign employee experiences to keep people engaged – all while fighting to stay ahead of the competition. If we needed an example of what a VUCA (volatile, uncertain, complex and ambiguous) world would look like, the last few years have clearly shown us that. 

How can companies successfully navigate such challenges going forward? We believe that the best way forward is to focus on innovation, first and foremost. By doing so, companies create the right kind of people-oriented cultures that not only boost revenue, but also improve other metrics like DEI or engagement. When viewed through the lens of innovation, cognitive-social-emotional skills like empathy or active listening take on a different flavor which make them far more effective in the workplace. 

Three trends show why an innovation-first strategy can be beneficial to organizations. 

Artificial Intelligence

ChatGPT showed that AI is advanced enough to do better than humans at certain tasks – even those that are more cognitively demanding tasks like writing essays or code. Let’s drill down a bit into one of the best paying jobs currently – software development. Using AI to help with coding is significantly improving developer productivity. Tasks that took several hours earlier, now can be done in a few minutes with a quality that is at par with the best programmers. That creates new  implications for technology-focused companies. 

Companies no longer need to hire as many people to do the work they need. Well funded companies spend tons of money recruiting talent from the most reputable colleges. With AI in the picture, this approach will no longer provide them with competitive advantage over smaller companies or scrappy startups who don’t have the resources to go after top talent in the same way. With AI that offloads most of the coding tasks, the difference between a talented developer and a mediocre one reduces sharply. 

Competitive advantage will shift to abilities that AI can’t handle well, creative thinking being an obvious area. Creativity requires the production of novel responses, which by definition implies the lack of existing data for algorithms to learn from. This is not to say that AI can’t do limited forms of incremental creativity, but they tend to be more “within-the-box” as opposed to more transformational “out-of-box” creativity. In other words, AI can rearrange existing content in new ways which may or may not turn out to be creative, but it can’t really synthesize new concepts.   

We recently tested OpenAI’s ChatGPT for several different creative prompts and our analysis shows that ChatGPT’s creativity is nowhere close to that of humans, including elementary aged children. It lacks the fundamental ability to do abstract thinking, so when posed with a challenge to invent something from two random objects, it tends to follow the simplest strategy of putting the two objects together. Or when asked to generate alternate endings to stories given a twist, it simply bails out. 

The obvious implication of the rise of AI, is that companies need to build their creative capacity in order to stay competitive. Companies that prioritize building creative thinking skills (like associative or reverse thinking), creating channels to harness employee innovation and most importantly foster an innovation-focused culture will emerge as the leaders of the next wave. 

Global Threats

Covid19 showed the extent to which a global threat can impact lives of people all over the world. With the world being more connected and more interdependent, a local event can have major consequences. Just in the last few years, companies have had to deal not only with the pandemic and its consequences, but also geopolitical issues like wars, unforeseen natural disasters and economic recessions. Such global threats are only expected to become more frequent. Needless to say, companies that can respond to such threats in a flexible and agile manner have a much greater chance of survival. 

However, the ability to be flexible and respond to changing environments in real time requires the ability to improvise and find novel solutions, to reconfigure existing resources and capabilities in new ways to solve problems, to collaborate in an open-minded way with others, to iterate when things don’t go as planned. In short, it requires the full arsenal of creative thinking capabilities deployed towards the crisis at hand. This ability to be innovative in the face of threats builds organizational resilience which significantly improves survival odds for any organization. 

To build a resilient organization, innovation has to become part of the company’s DNA. Building a culture of innovation involves deliberately building core cognitive capabilities, allowing ad-hoc collaborations to take place without unnecessary friction and creating formal structures for capturing employee creativity. 

Management Complexity

Managing a large workforce today is complex with many initiatives like employee engagement, talent retention and DEI (diversity, equity and inclusion) taking up valuable time and energy. However, when organizations look at these as separated, isolated aspects they can inadvertently create conflicting processes and norms. This affects not just leaders but also employees, who feel like they are being pulled in different directions while having to maintain high levels of productivity. 

One possible solution is to view such initiatives through the lens of innovation, which is the primary goal for any company, and identify ways to streamline and simplify. As an example, we conducted a study recently to understand the impact of gender bias on innovation within the technology industry. We found that by adopting a few universal strategies, like enhanced group decision making processes, companies can improve overall innovation while reducing the impact of bias. The advantage of using innovation as a means to reduce bias is that it removes the salience of gender or race. One of the key reasons diversity programs are ineffective is that they bring race or gender sharply into focus, thereby reinforcing the stereotype even more. Ironically, the most effective diversity programs aren’t specifically designed for diversity. This is not to say that all DEI initiatives can be made redundant, but by finding synergies it is possible to do more with less.  

Using An Innovation-First Approach 

An Innovation-First approach is a way to streamline and consolidate multiple goals in a way that optimizes the primary goal of innovation and productivity. It’s a way to refactor company cultures to remove redundant, conflicting or ineffective processes and orient the entire  organization towards a common purpose. As a result, companies create healthier organizations where both employee engagement and profitability is high. 

For the last several decades companies have focused narrowly on employee productivity, which works for linear and predictable workloads. However, with the current trends in AI, automation and globalization, this is no longer enough. Companies that can successfully adopt innovation will gain a significant competitive advantage over their rivals.

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ChatGPT Is Smart But It’s Not Creative

Since its recent launch, ChatGPT, a large language model AI, has caused quite a stir in the technology industry and the broader community at large. Its capabilities have sparked both awe and alarm – an AI that is so good at what it does that it has real potential of displacing people at work. But how worried should we be?

Let’s first get the obvious stuff out of the way. ChatGPT is an incredible tool and exceptionally good at some tasks like producing code, compiling essays and even writing poetry. However, when it comes to creative thinking, it misses the mark. 

To understand if it can produce creative ideas, we asked ChatGPT a few brain teasers that we routinely use in our workshops, even with early elementary age kids. They are typically used as 5-minute warm-up group activities that help to illustrate the underlying cognitive mechanism. 

At a fundamental level, we know that AI tools have limited creativity because AI relies on using massive amounts of prior data to learn. But creativity requires you to think of novel ideas that don’t yet exist and therefore don’t have any data to learn from. Nevertheless, it’s still possible to generate somewhat of a creative output in some areas like art as we have already seen with tools like Midjourney. So, let’s take a deep dive at how ChatGPT fared with these exercises. 

Associative Thinking

To test ChatGPT’s ability for associative thinking, we tried the Wacky Inventions brain teaser. The idea behind this brain teaser is to use our brain’s natural associative processes to combine unrelated objects and make a new invention. One can argue that this associative ability is perhaps the most fundamental aspect of creativity. A real world example of associative thinking is Google’s PageRank algorithm that completely transformed what search engines could do. It combined the concept of academic citations (articles that are cited more indicate more authoritative sources) with websites – two completely unrelated domains – to create an automated way to assess the quality of a website. 

We posed random combinations of objects that we have encountered in our sessions to make it easier to compare ChatGPT to human performance. Here are two examples:

Example 1

Q: What new invention idea can you come up with using a table and a scarf?

A: A portable table with a built-in scarf storage system. The table has a small drawer or compartment on the side that is specifically designed to hold scarves. The scarves can be easily rolled up and stored in the compartment, allowing users to keep their scarves organized and easily accessible. The table also has a built-in hook or hanger on the side, allowing users to hang their scarves on the table for easy access and display. This invention would be especially useful for people who have a large collection of scarves and need a convenient way to store and access them. It would also be useful for people who need a portable and versatile table for various activities, such as crafting, sewing, or organizing.

Q: That’s a good idea! Can you find a way to use an attribute of the scarf to make a new kind of table?

A: A table with a built-in scarf-covered surface. The table has a removable and interchangeable scarf that covers the top surface of the table. The scarf can be easily swapped out for different styles and colors, allowing users to customize the look of their table. The scarf can also be used as a protective layer for the table, preventing scratches or damage to the surface. This table would be especially useful for people who want a versatile and customizable piece of furniture for their home. It would also be useful for people who want a protective and stylish table for activities such as crafting or sewing. Additionally, the scarf-covered surface would add a cozy and comfortable feel to the table, making it a great addition to any room.

Q: That’s great! What property of the scarf are you using in your invention idea?

A: The property of the scarf that I am using in my invention idea is its ability to be easily removed and swapped out for different styles and colors. This property allows users to customize the look of the table and create a unique and personalized piece of furniture. It also allows users to easily update the look of the table by swapping out the scarf for a different color or pattern. Additionally, the property of the scarf being removable and interchangeable allows for easy cleaning and maintenance of the table surface.

Example 2

Q: What new invention idea can you come up with using a football and a water bottle?

A: A portable football water dispenser that attaches to the top of a water bottle. It has a small spout on the side that allows players to easily hydrate during a game without having to stop and open the water bottle. The dispenser is designed to fit snugly on the top of the bottle, with a secure fastening mechanism to prevent it from falling off during use. It also has a built-in straw that allows players to easily drink from the bottle without removing it from the dispenser. This invention would be especially useful for athletes who need to stay hydrated during long and intense games.

Q: So is this a water bottle with a football shaped dispenser on top? 

A: An error occurred. If this issue persists please contact us through our help center at help.openai.com.

Example 3

Q: What new invention idea can you come up with using an umbrella and a jump rope? 

A: An error occurred. If this issue persists please contact us through our help center at help.openai.com.

We gave a few other combinations and found that a common theme in ChatGPT’s responses, purely from an outcome perspective, is that it combines the two objects physically – attaching the two together for increased functionality. This, in general, is a reflection of a low level of creativity similar to very young children. However, as children get better at abstract thinking, they naturally start using the objects as starting points and zero in on a couple attributes that they can seamlessly integrate in the invention. Explicitly nudging children to use an attribute of the object is also effective in helping them to get more sophisticated solutions, and in general improves their abstract thinking skills. Unfortunately, ChatGPT wasn’t able to find the right property to work with as was evident in the first example. “Removability” isn’t really a property of the scarf. What it did instead is used instances on the internet where the two object names appear together (you can google “table scarf” to see some results) and cobbled together a reasonable sounding paragraph. But it doesn’t really understand what it created. In the second example, when asked a clarifying question it ends up bailing out with an error message. 

The problem is that ChatGPT isn’t really equipped to do abstract thinking. Think about how humans build a model of the world around them. Babies and toddlers spend hours interacting with objects around them – they touch them, taste them (much to our frustration), hit them, shake them and toss them. These adorable, uncoordinated actions serve a very useful function – they help children create an internal representation of the object. This step is crucial for their development because without building these internal models, children have a harder time imagining and creating new combinations in their heads as they grow older. It’s the primary reason why play is essential for long-term creativity. 

But that’s not all. We don’t just build standalone models but also much more extensive associative networks where different concepts are connected to each other through different properties. For example, the concept of “strawberry” in your brain might be connected to “red” by a thing-to-property link or connected to a “rash” by a cause-effect link if you are allergic to strawberries. Every new thing a baby learns is continually being mapped into this giant associative network of different objects, concepts and ideas. This extensive and rich associative network is what allows us to make abstractions, hop from one concept to another, and make novel connections. 

We use this rich implicit knowledge built over many years extensively when we come up with novel ideas. Even when we see new ideas from others, we can quickly adapt them to our situation, because of this underlying layer of implicit knowledge that we don’t pay conscious attention to. The challenge with scouring the internet is that a lot of this implicit knowledge doesn’t exist there. On the internet it’s assumed that when someone talks about a scarf people know what that is – you won’t necessarily find places where attributes of a scarf are listed that allow it to be connected to other concepts that are further away.  

This is of course a logical model and not a physical one inside our brains. We know very little about how association takes place inside our heads but the logical model gives a good approximation. Most creativity techniques leverage this and simply provide triggers to the brain (where the real magic happens) to get new ideas in a somewhat reliable fashion. 

In the third example, the associative distance between the two objects (umbrella, jumprope) is high meaning that you typically don’t see them mentioned together, so ChatGPT simply bails out again. In contrast, using the same two objects, a group of 4th-5th graders came up with the idea of an umbrella shaped water ski where you can sit and relax, while being pulled by a rope.

Additional Creative Thinking Triggers

We also tried a few other kinds of brainteasers like Opposite Day and Twist-a-Story to see how ChatGPT handles them. The idea behind Opposite Day is to reverse a well known assumption which can lead to radically new insights. For example, the designers of the portable toddler chair that attaches to any table, came up with that idea by asking themselves “What if a chair didn’t have any legs and why would that be useful?”. In Twist-a-story, the idea is to find an alternate ending to an existing story by changing some element of the story. 

Here is how ChatGPT answered these brain teasers.

Example 4

Q: What if libraries didn’t carry books? What would they have instead and why would it be useful?

A: If libraries didn’t carry books, they would likely carry a wider variety of media such as e-books, audiobooks, and digital media. This would be useful because it would allow users to access a wider range of content, including both fiction and non-fiction, in a variety of formats. It would also allow libraries to provide access to more up-to-date and current content, as e-books and digital media are often released more quickly than traditional print books. Additionally, it would save space and resources, as digital media can be stored and accessed more efficiently than physical books.

Example 5

Q: Have you heard the three little pigs story?

A: Yes, I have heard the story of the three little pigs. It is a popular fairytale about three pigs who each build a house to protect themselves from a wolf. The first pig builds his house out of straw, the second pig builds his house out of sticks, and the third pig builds his house out of bricks. The wolf is able to blow down the first two houses, but the third pig’s brick house is strong enough to withstand the wolf’s huffing and puffing. In the end, the third pig is able to outsmart the wolf and keep him out of the brick house.

Q: What if the third pig runs out of bricks while making his house and the wolf shows up? How would the story end then?

A: I’m sorry, but I am not able to browse the internet to provide you with an alternate ending to the story of the three little pigs. As a large language model trained by OpenAI, my knowledge is limited to what I have been trained on, and I do not have the ability to browse the internet or access new information. My knowledge cutoff is set to 2021, so I do not have information on events or stories that may have happened after that date.

Let’s briefly dissect ChatGPT’s responses to these additional brainteasers. 

In example 4, ChatGPT gives us a rather unimpressive answer about using a wider variety of media, which most libraries already do. Once again, it’s not able to extract the more general feature of a library – allowing people to borrow things. When the same challenge is posed to people, they quickly arrive at this insight and start thinking of additional items that aren’t used often, or are cumbersome to own, and would make good candidates for borrowing. Using this kind of analogical thinking they come up with ideas like libraries for power tools, folding tables and chairs, or formal clothes. 

Finally, the last example clearly highlights ChatGPT’s limitation when it comes to thinking of original solutions. In all fairness, ChatGPT was never designed for creative work so this is not surprising. 

Humans Vs. Bots

So should we be worried about AI taking over jobs? Yes, absolutely! There is no doubt that AI is going to start taking over more and more tasks that depend on linear thinking models, where lots of training data exists. Even for white collar jobs like software development, ChatGPT is proving to be valuable in improving developer productivity. So companies will soon need to hire fewer people for the same workload. 

However, ChatGPT currently can’t handle creative work and come up with novel ideas. It is theoretically possible for AI models to build richer data and limited abstract reasoning capabilities, so we should expect next generation tools to display more creativity than currently possible. In the short term however, we can safely assume that creative thinking is going to be a strictly human capability. 

So, where does this lead us? 

The natural solution (and one that’s been around for a long time) is that humans work together with technology to leverage each other’s strengths. In this ideal scenario, AI takes care of time-consuming tasks to improve the productivity of humans, freeing them up for creative tasks that only humans can do. If we accept that premise, then it follows that a sustainable long-term advantage, both for individuals and organizations, will be their creativity and innovation. In reality, this won’t happen without deliberate effort, and the short term will almost certainly be a lot messier with job disruptions. Creativity among students has been declining for some time now which makes them unsuitable for changing work, and companies are not necessarily ideal places to harness employee innovation. Without improving both of those aspects, our journey towards the ideal scenario can end up becoming needlessly rocky.

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The Most Essential Organizational Capability For Crisis Management

With the terrorist attack of 9/11, US airlines were suddenly faced with a black swan crisis. The entire airspaces of US and Canada were shut down for 48 hours by federal order, and when civilian air traffic resumed it was significantly limited. Despite billions of dollars in federal assistance to cover for lost revenue the airline industry continued to lose millions of dollars per day. To curb this loss, major airlines cut their flights by an average of 20% and laid off an average of 16% of their workforce. 

Two airlines – Southwest and US Airways – that both focused on short-haul flights and therefore faced disproportionately higher travel disruptions, adopted very different strategies during the crisis. US Airways had the highest level of layoffs in the industry at 24%, while Southwest went the other extreme and did not lay off any employees. Four years after the crisis event, their performance couldn’t be more different. Southwest Airlines had the fastest performance recovery and regained 92% of its stock price pre-911 while US Airways could only achieve 23%. 

So why did Southwest rebound back so strongly after the crisis?

The key, as researchers discovered, was organizational resilience. Southwest by retaining all their employees had the right combination of resources to find creative ways to reduce costs and improve productivity. When organizations lay off people purely by numbers, they not only lose individual expertise, they also lose intelligence that emerges from the relational networks that employees were part of. These networks are hard to rebuild even when they hire new people at a later time. 

One way to think about this is that people build both strong and weak relationships at work. Within their immediate groups they go through the forming, storming and norming, to finally reach the performing phase. In the process they build a deeper understanding of each other and their respective strengths. Beyond their current and past teams, they also build weaker relationships with others in the company over time. So they might know that Joe over in marketing has great relationships with client companies or Jane in accounting is a spreadsheet wizard. In a crisis situation these insights and information end up being especially valuable, as people reorganize themselves and try creative approaches to meet the challenge. Disrupting these relationships harms the ability to innovate and problem solve in an emergency. As the research paper explains, “Paradoxically, a common organizational response to crisis–i.e., layoffs–tends to undermine the very relationships that help organizations cope during periods of crisis.”

Organizational resilience is the ability to bounce back from a crisis to achieve a new stable point. The ability to withstand disturbances can be viewed as a spectrum with fragile at one end and antifragile at another. A fragile system is one that is unable to handle the challenge, much like US Airways that eventually went through two bankruptcies before finally merging with American Airlines. The next step up is a robust system that can absorb a set of known disturbances and comes back to the original stable point. A resilient system goes a step further – it can absorb unknown stresses by landing at a different desirable point of stability. Finally, an antifragile system is one that bounces back to a new stable point which is better than the previous one. In other words, an antifragile system takes the chaos created by the crisis and emerges stronger than before. 

Resilient and antifragile systems allow one to thrive in uncertain conditions, which is becoming increasingly important. As companies face more volatile environments with frequent natural, geopolitical and other disruptions, building organizational resilience is becoming essential. 

So how does one consciously build a resilient and antifragile organization? There are three main areas to consider – creative thinking, group coordination and organizational mindset.  

Creative Thinking

An unexpected crisis requires new ways of thinking and doing things since the crisis brings a new environment and constraints with it. So, the foremost principle is bricolage – the ability to improvise and find creative solutions. Organizations become less vulnerable if they are able to recombine existing resources, processes and expertise to create novel solutions. Ducheck, who researches organizational resilience, captured this essence with “What first sounds counterintuitive—to improvise in already chaotic situations—can help to prevent catastrophe.”

However, you can’t turn on a faucet and expect creativity to flow if the underlying plumbing was never installed. Creativity has to be in the company’s DNA – a core part of its culture. Without a creative culture, companies might occasionally get lucky with dealing effectively with a crisis, but it’s not a long-term sustainable solution. Instead what  organizations need to build is strategic resilience – the capacity to continuously anticipate and adjust practices in order to meet incoming challenges. And one way to do that is through well-integrated innovation programs that tap employee creativity. Such programs surface ideas from frontline employees that are valuable but often ignored. Taleb, who coined the term antifragility, goes a step further with, “If about everything top-down fragilizes and blocks antifragility and growth, everything bottom-up thrives under the right amount of stress and disorder.”

In their HBR article, The Quest for Resilience, Hamel and Välikangas point out two mistakes that companies often make when they build employee innovation programs. 

First, companies often focus on a few big bets instead of funding many small bets. The problem with that approach is many high potential ideas get stymied early on, so companies don’t capture the full benefits of employee innovation. Additionally, the lack of variety in ideas makes companies less resilient in the long-run. Equally importantly, big bets leave rank and file employees out of the innovation cycle depriving them of opportunities to practice creative thinking. The authors recommend that “a reasonably large company or business unit—having $5 billion to $10 billion in revenues, say— should generate at least 100 groundbreaking experiments every year, with each one absorbing between $10,000 and $20,000 in first-stage investment funds.”

Second, when companies do introduce formal innovation programs they create innovation ghettos, separate from the regular day to day work. For example, hackathons or incubators where people work on ideas (sometimes for a very short time) that are outside the core and don’t really change the company bottom line. What companies need, instead, is an innovation pipeline that is integral to the work people are doing like what Whirlpool is doing. In the 1990s, Whirlpool made innovation a core competency and recruited a big part of their workforce to search for breakthrough ideas. By training people and creating tools to track innovative ideas, they institutionalized the process of innovation for their company.   

Collaboration

To successfully deal with crises, teams often have to self-organize into ad-hoc networks that pull in the right set of expertise and skills. Organizations that allow easy collaborations across groups on a regular basis are more adaptable to challenges than organizations that are siloed. Collaborations across immediate groups or divisions, expand resources that can be used and improve the capacity to respond to the event. 

But getting the right people together is not enough to solve complex problems if people lack the cognitive and interpersonal skills to take each others’ ideas and synthesize a novel solution from them. Breakthrough ideas emerge from egalitarian groups where people actively listen to each other’s ideas and consciously make an effort to integrate different perspectives. 

Reducing bureaucracy towards inter-group collaboration and building the right teaming skills (both cognitive and social-emotional) make organizations flexible and nimble when unexpected events shake things up. 

Mindset

Most people assume that resilience is fueled by optimism. However, optimism by itself can be dangerous – it leads to toxic positivity, hubris and blind spots. Instead, resilient organizations display hopefulness which can be described as simultaneously holding two beliefs – that their systems are not infallible and that they have the competency to find solutions when things do fail. Vagus and Sutcliff define this hope as “a confidence grounded in a realistic appraisal of the challenges in one’s environment and one’s capabilities for navigating around them.”

This mindset at the organizational level is driven by leaders and filters down to rest. It requires a culture of humility that takes its prior successes lightly. It requires people to continually question their products and environment, and proactively address things before they become issues. Fragile organizations, on the other hand, place a low priority on such proactive work (e.g. “if it’s not broken don’t fix it” or “convince me this is an issue”). 

Building the right mindset within an organization goes hand in hand with building creative thinking and collaborative skills. People need to personally experience their collective ability to manage disruptions, without which leadership’s assertion of internal capability will sound hollow. 

Conclusion

No one could have predicted the Covid19 pandemic and the disruption it would create a few years ago. As the world continues to get more connected and more complex, unexpected threats continue to rise. While we can’t predict a specific threat, we can expect to face some crisis in the near future. Whether a company crumbles under the pressure of unanticipated threats or emerges stronger than before depends on its level of organizational resilience. Unfortunately, many companies inadvertently do things that reduce their resilience – they undervalue people’s creativity and relationships, they push down directives from the top instead of encouraging bottom-up problem solving, they reduce communication which thwarts collaboration and they fail to deploy the right kind of resources. Resilient organizations flip traditional organizational theory on its head and deploy cognitive, relational and financial resources instead of restricting them. They create cultures where employee creativity is valued, because unexpected threats require unexpected solutions. They recognize that much like marathons, organizational resilience depends on training before the crisis event.  As Herb Kelleher, the founder of Southwest Airlines, said, “If you create an environment where the people truly participate, you don’t need control. They know what needs to be done and they do it.“

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The Specific Type Of Empathy That Is Highly Beneficial In The Workplace

When people talk about the role of empathy in innovation, they usually mean using empathy as a means of discovering problems that are worth solving. The entire field of design thinking is predicated on using empathy as the first step to uncover problems another person is facing. By putting yourself in another’s shoes, one can more accurately determine what they might be going through in a particular situation which in turn helps in devising new solutions. 

Empathy is indeed one of many routes for creative ideas, but the connection between empathy and innovation is much more intertwined than simply being a trigger for discovering problems. 

What Is Empathy?

Empathy is described as “a complex psychological response in which observation, memory, knowledge, and reasoning are combined to yield insights into the thoughts and feelings of others.” In the empathetic state, there may be some temporary identification with the other, but at no point is there any confusion between the self and the other.

Research indicates that there are two empathy mechanisms – a basic emotional system and a more advanced cognitive perspective-taking system. These two systems use different neural pathways and can get triggered in parallel. Emotional empathy is when you instantly feel the same emotions that the other person is feeling even when you don’t know their whole story, and one theory attributes this to the presence of mirror neurons in our brain. For example, seeing strong emotions like fear or distress on another person’s face can instantly create the same emotion inside us. Cognitive empathy, on the other hand, is about taking the other person’s perspective in order to determine how they might be thinking and feeling in a situation. It is based on conscious reasoning and while emotions are still generated, they are more controlled. 

As an example, say one of your employees shares a stressful family situation. With emotional empathy, you detect his stress and immediately experience the same emotion. This sudden burst of emotions might cause you to relive a time when you went through a similar situation which in turn further amplifies those feelings. In the cognitive empathy case, cognition takes the lead and you focus on understanding your employee’s perspective. You actively try to recall a similar situation you faced before along with its associated challenges, which gives you insights on what your employee might be worried about even when those aspects are not verbalized. 

One way to distinguish between the two types of empathy is that emotional empathy is about “I feel what you feel” while cognitive empathy is about “I understand what you are thinking.” And it turns out that of the two, cognitive empathy has some surprising benefits in the workplace. 

How Cognitive Empathy Improves Innovation and Decision Making

One of the immediate benefits of cognitive empathy is that it puts one in a problem solving mode and allows one to come up with more novel solutions. With emotional empathy on the other hand, the cocktail of emotions often makes it harder to focus on finding solutions. 

The reason cognitive empathy is so effective is that it relies on perspective taking, which also happens to be a key mechanism for creative thinking. In perspective taking, one has to temporarily drop their own way of thinking (which reduces self-bias), and instead pay attention to the other person’s point of view. Integrating multiple perspectives leads to new insights about the problem as well as novel ways in addressing them. 

Perspective taking also underlies good listening skills because the ability to analyze and integrate a conflicting mental model from another demonstrates to them in a very concrete way that their ideas have value. For similar reasons, cognitive empathy shows superior results when it comes to negotiating. In a series of experiments involving MBA students, researchers found that perspective-takers were able to uncover underlying interests and generate more creative solutions with greater collective and individual games than emotional empathizers.  The authors summarized, “that in mixed-motive interactions, it is better to ‘‘think for’’ than to ‘‘feel for’’ one’s adversaries—more beneficial to get inside their heads than to have them inside one’s own heart.”

The benefit of practicing cognitive empathy extends well beyond isolated incidents – adopting perspective taking as a habit allows innovative ideas to emerge from routine discussions. As people become more cognitively empathetic, the overall creativity and innovation levels of an organization increases. Empathetic leaders play a crucial role in the process of building organizational innovation. A recent study found that people with highly empathetic senior leaders were 4.7x more likely to report being innovative at work compared to people with less empathetic senior leaders.

How To Build Cognitive Empathy

A more recent model of empathy based on brain lesions suggests that the two empathic systems are independent and are simultaneously triggered. Using cognitive empathy in any situation therefore requires striking the right balance between emotions and problem solving. Here are three things to keep in mind for cognitive empathy:

  • Concern For Others: The first step towards cognitive empathy starts with a genuine concern for others. Without this, any attempt to demonstrate empathy will come across as inauthentic. Having a prosocial motivation has been shown to encourage perspective taking and enhance overall creativity of solutions.
  • Maintain Self Awareness: A key challenge in perspective taking is the egocentric bias. We see others through our own beliefs and knowledge, making it hard to fully understand their perspective. A degree of self awareness can help overcome the egocentric bias by deliberately suppressing our own mental models. Self awareness is also useful in regulating emotions and keeping the focus on problem solving. 
  • Build Perspective: Finally, the goal of cognitive empathy is to understand the other’s perspective in order to find effective solutions. The easiest situation to relate to is one where you have had a similar experience but if that doesn’t apply, then several other cognitive techniques can help. You could use abstraction to find a situation that uses the core emotion (e.g. anxiety but in a different scenario), use counterfactual thinking (“what if..”) to imagine how you would feel in a similar situation or use associative thinking to piece together different experiences into a new scenario. Consciously constructing a relevant scenario can then give insights on what the other person is dealing with and how to improve the situation. The same cognitive techniques that help build perspective are also core to creative thinking so practicing cognitive empathy regularly increases cognitive flexibility and problem solving skills.

Conclusion

Cognitive empathy is the mental capacity to take another person’s perspective where the goal is not to experience the other person’s mental state but to understand it better. That understanding allows one to gain insights into aspects that people may not be verbalizing. Cognitive empathy is not just useful in a specific situation –  it increases mental flexibility and problem solving skills more generally. The more people practice cognitive empathy in an organization, the more they become better at creativity due to shared cognitive mechanisms. 

This is not to say that emotional empathy has no value. Being able to pick up and reflect others emotions helps in relationship building and is likely more valuable in the long-term than in the short-term. However, as the nature of work shifts more towards hybrid and remote where it’s not always possible to pick up on nonverbal cues that trigger mirror neurons, the role of cognitive empathy becomes much more important. 

By consciously incorporating cognitive empathy, organizations can become both kinder and smarter. 

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The Most Important Element For Being A Good Listener

Being a good listener is essential to communication and active listening is increasingly considered to be a vital leadership skill. A quick internet search on how to be a good listener serves up countless articles with similar advice – giving your full attention to the speaker, repeating back what the speaker says or asking lots of questions. While these tips are useful to some extent, they don’t really address the most crucial aspect of listening. They place more importance on how to look like a good listener as opposed to being one, and miss the essence of listening. 

Real listening is a cognitive skill.

A Model Based Approach To Listening

To understand why listening has a strong cognitive component, let’s consider a scenario that can make or break your image as a good listener – when people disagree with you. This kind of situation plays out quite frequently in the workplace. One person thinks that feature A (or task A) is more important to address while their colleague thinks that feature B (task B) is more important. 

Most people approach a disagreement with the mindset that they need to “win” the debate and focus on vigorously defending their idea. But this is the wrong attitude to start with and a better approach is to think in terms of mental models. 

Assuming that there are no strong biases at play, one reason two rational people might disagree is that they have two different mental models of how the (small slice of) world works. Different mental models are a reflection of the fact that different people bring different knowledge and experiences with them that has shaped their thinking.  

Viewed from that lens, active listening is a problem solving exercise in reconciling the different mental models. There are only two possible outcomes – one person has a better model which leads to the other updating their mental model, or both people have an incomplete picture which leads them to co-creating a better, more holistic model. For successful listening to take place, at least one mental model has to be updated. 

How To Listen Thoughtfully

The key to better listening is to focus on the cognitive aspect of listening as your main goal. Here are three things to keep in mind as you engage in active listening:

  • Start With A Problem Solving Mindset: If someone comes to you with a viewpoint that is different from yours, start with the assumption that their viewpoint is valid based on their knowledge or prior experience. In most cases, we jump into the dialogue in a critiquing mode, trying to find holes in the other person’s thought process in order to “win” the point. Instead, reframe the discussion as a puzzle where multiple perspectives need to be rationalized and synthesized into a more complete model.
  • Explore Mental Models: Ask questions to understand each other’s mental models and explore their boundaries. Are there specific scenarios where one model is a better representative? As a leader, it’s tempting to feel that you have a better understanding of the problem and thereby miss questioning your own assumptions. While this might be true for simpler issues, for more complex problems you can safely assume that both people have an incomplete picture. 
  • Don’t Rush To Finish: Synthesizing different perspectives is a cognitively demanding task and for complex problems the right solution may not emerge in one discussion. Some of the most creative ideas come when you take a break after thinking intensely about a problem. So become more comfortable with deferring the decision to allow for more bake time. 

One Simple Question To Ask Yourself

If you have been diligently following rules of thumb for good listening and wondering why your team still doesn’t think of you as a good listener, it’s time to recognize that performative listening doesn’t work. Blindly following “listening rules” make interactions seem contrived and fast tracks you to losing trust with your team. 

Instead, focus on the cognitive aspect of listening and allow other behaviors to flow naturally from that. When people are genuinely trying to understand, they ask more relevant questions that can reconcile different viewpoints and increase collective intelligence. They come across as authentic because they are not asking (any) questions just to appear interested. Similarly, understanding different perspectives and integrating them into your mental models is a cognitively demanding process. As a result, good listeners tend to talk less because they are doing more complex information processing internally, not because they are following a rule in order to appear interested. 

If you are not sure whether a discussion went well or not when it comes to active listening, ask yourself one question – did your mental model change? 

For a productive conversation, at least one person’s mental model needs to change and in the ideal scenario, both parties get an “aha” moment that adds to their understanding. With the model based approach, listening and learning become indistinguishable. 

Nothing makes someone feel like they were heard more than having their idea be a clear part of the solution. But achieving that is not easy in the workplace due to poor listening habits. The main problem with the prevalent guidance on listening is that it focuses on how good listening looks on the outside, and not on what is happening inside where the real work gets done. It misleads people into believing that simply following these rules of thumb will make them a better listener. By adopting a more problem solving mindset where you actively try to understand and integrate each other’s mental models is a more constructive and effective approach to listening. 

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Harnessing Group Intelligence For Innovation Productivity

Edward DeBono argued three decades ago that creativity is the most important human resource of all, and it’s truer now than ever. Without a strong culture of innovation that harnesses employee creativity effectively, organizations are much more likely to fail in the modern economy.  

But capturing employee creativity towards organizational innovation is challenging. Our current management practices evolved from Fordist (and Taylor’s scientific management even earlier) approaches to measuring productivity that served well for linear, predictable systems. For example, if a production line produces X widgets/week, you could be sure that by adding another production line you can get 2X widgets/week. Unfortunately, applying these approaches to innovation doesn’t work for two reasons:

  • Creativity is fundamentally non-linear. During brainstorming two people with individually weak ideas might discover key insights that lead to a billion dollar one. Or, an individual could be wrestling with a challenging problem for several days with very little to show for it and then suddenly find an interesting solution in a day. 
  • Complex problems often require a group to collaborate in order to find efficient solutions. But simply bringing people is not enough. Depending on the group and how individuals interact, you could get collective intelligence or collective stupidity. Most incentives are aligned with individual performance and backfire when work is highly dependent on group performance. 

So instead of focusing on linear metrics like bugs fixed per week or number of features shipped, we need better mechanisms that allow for collective intelligence to flourish. 

Swarm Intelligence

Some of the most fascinating examples of complex problem solving in groups come from nature. Groups of ants, bees, birds and other creatures can solve surprisingly complex problems easily even though each individual in the swarm is only following simple rules. Intelligent behavior emerges from these simple interactions. For example, army ants can travel for long distances without traffic jams in dense three lane highways by following simple rules like outgoing ants turn aside when they encounter incoming ants. 

Collective intelligence works surprisingly well in many kinds of problems like estimation or prediction. One of the most well known examples comes from Francis Galton, a pioneering statistician and half-cousin of Charles Darwin, who asked people to guess the weight of an ox at a fair in 1906. While individual responses varied from 1,074 to 1,293 lbs, the mean came to 1,197 lbs closest to the true value of 1,198 lbs! 

Group intelligence also outperforms individual intelligence in much more complex situations like hiring the right candidate for a role. Google at one point had a fairly complex hiring process where candidates could face up to 25 interviews. After analyzing data on interview performance and subsequent job performance, they were able to simplify the process down to 4 interviews which gave them an 86% confidence level. The interesting thing that came out of their analysis was that none of their managers – regardless of the years of experience under their belt –  were individually good at predicting who would make a good employee. The wisdom of the group of four always outperformed individual prediction! 

Research from several domains shows that for groups to work intelligently, few key conditions need to be met:

  • Individual members must be well-informed about their area to have a better than 50-50 chance of getting the right answer.
  • Cognitive diversity of the group is important. 
  • Individual members have to think independently and not influence each other’s opinions. 
  • Individual members should be unbiased.

Most organizations spend incredible amounts of time trying to find the most qualified candidate with the right set of domain skills during hiring, so the first criteria is often not an issue. The remaining three criteria often get underestimated (or ignored) which limits the amount of innovation companies produce.

Cognitive Diversity

The kind of diversity important in complex problem solving is cognitive diversity which includes knowledge (people skilled in different domains), perspectives (different ways of viewing a problem) and problem solving approaches (different heuristics or ways of generating solutions to the problem).

Cognitive diversity is correlated with diversity based on common factors like gender, race or ethnicity. Companies that prioritize increasing diversity have a better chance of being innovative and real-world results back that up. More diverse and inclusive companies are 1.7 times more likely to be innovation leaders in their industry. Scott Page, complexity scientist and author of The Difference, captured this perfectly when he said, “being different is as important as being good.”

Independent Thinking

Perhaps the most important criteria for harnessing group intelligence is for individuals in a group to think independently and not be swayed by others opinions. Unfortunately, this is also one criteria that most groups don’t pay attention to. When groups get together without adequate preparation, a few people might dominate discussions or people might be overly influenced by their leaders’ opinions. In such situations, decisions quickly fall prey to groupthink. 

To mitigate this, individual members need to think about the problem at hand and commit to their ideas and reasoning before they share with the group. This makes a huge difference in the quality of decision making. Despite the popularity of traditional brainstorming, groups that engage in nominal brainstorming (where people brainstorm individually before sharing with the group) come up with twice as many ideas overall and more original ones. 

Unbiased Thinking

Groups also suffer from biases which include both stereotypical (like gender) or cognitive biases. Hiring a more diverse workforce can mitigate the effects of stereotypical biases but cognitive biases can still remain. Two common cognitive biases are myside and one-sided thinking. 

Myside bias results from people’s inclination to favor arguments that support their opinion while ignoring or minimizing contradictory viewpoints. Organizational cultures where “defending your idea” is deemed an important leadership trait accentuate this bias.

One-sided thinking is our preference for arguments that are one-sided rather than those that offer multiple perspectives. A one-sided solution appears simpler and cleaner, and because it causes less cognitive strain, it’s more persuasive. As a result, leaders are easily swayed by a person who presents a simple argument compared to another who presents a more nuanced view. 

Useful Strategies

Groups can be smart or dumb. It’s easier now to see why groups end up with harmful outcomes in the age of social media where most, if not all, of the conditions get violated. Organizations can avoid some of these pitfalls and create a more innovative culture by implementing the right norms and incentives. Here are a few strategies to consider:

  • Hiring a diverse workforce is necessary but it’s not sufficient. Without implementing good systems where diverse viewpoints are included in decision making, one can’t reap the benefits of diversity. Despite the focus on DEI, inclusion from the perspective of innovation is still an issue among many companies. 
  • Creating the right norms for decision making are important when it comes to ensuring independent and unbiased thinking. The Build, Teardown and Rebuild (BTR) method is one such example that removes biases from decision making in groups and can be implemented relatively easily. 
  • Ensure that your incentives and metrics don’t create the wrong kind motivations when it comes to contributing to groups. Complex problem solving is an emergent property when groups follow certain conditions. It requires individuals to behave in prosocial ways that are often at odds with incentives which encourage individual performance at the expense of group benefit. 

Complex and creative problem solving is a highly social problem. What gets created in any company – code or product or service – is heavily dependent on the people that come together to solve the problem. In such an environment, social engineering is as important (if not more) because how intelligent a group behaves depends on how the group interacts and problem solves. Creating the right processes and incentives can improve a company’s innovation throughput and set them on a competitive path.

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Creativity Hack: Reframe A Challenge

Reframing a problem is an effective way to come up with new ways to solve the problem. However, many times people end up rewording the problem instead of reframing it in a broader context. At a cognitive level, reframing is related to abstract thinking which underlies creative and complex problem solving. Abstract thinking allows one to get to the essence of a problem. 

About The Hack 

To reframe, find the higher level of abstraction of a problem or an activity. A higher order abstraction typically fits the pattern “[description] by [activity]” while a lower level of abstraction fits the pattern “[activity] by [description]”. For instance, if the activity is ‘reading a book’, a high-level description could be ‘relaxing’ (“I [relax] by [reading a book]”) while a low-level description could be ‘flipping pages’ (“I [read a book] by [flipping pages]”).

As a real word example, what if your challenge was to improve the coffee experience? Without trying to reframe the problem one might be tempted to focus on the quality of the coffee beans or new blends that might appeal better to customers. And in fact, this was the direction Starbucks was taking till Howard Schultz, who later became the CEO, went to Milan on a buying trip for the company. 

In Milan, Schultz got deeply inspired by the vibrant coffee culture. Espresso bars with trained baristas making cappuccino and other drinks from high quality arabica beans were everywhere. People met at these local espresso bars to connect with their friends or to discuss various issues. The social experience and the sense of community was so entwined with coffee as a drink. Schultz’s determination to bring that vibe and culture to the US led to the explosive growth of Starbucks. While Schlutz didn’t deliberately use reframing, the fortuitous trip became a catalyst for him to take the broader view and realize that people “socialize by drinking coffee”.  

While a higher level of abstraction can open up new avenues of thinking and more transformational ideas, lower levels of abstraction are also useful. They can help identify incremental improvements that might also be useful to implement.

Summary

Finally, here is a quick summary of the creativity hack and how to use it.

DescriptionReframing challenges can open up new possibilities and lead to more transformational ideas. Reframing isn’t about rearticulating the problem. Instead it involves moving to a higher (more general) level of abstraction. To reframe the problem, cast it in the form “[description] by [activity]”.
ExampleSuppose your challenge is to improve libraries and encourage people to read more. A higher level of abstraction could be “I get intellectual stimulation by reading ”. By focusing on intellectual stimulation, you might get a different set of ideas — book clubs, puzzle nights — which can be used to attract more people to the library.
Tips – A higher level abstraction corresponds to “why” while a lower level abstraction corresponds to “how”
– A common mistake is to change the goal and/or the subject while reframing. For example, deciding what product to build for the customer might start with what the customer is trying to achieve but end with “to make money for my company” which is an incorrect reframing.
ExtensionsThis technique can be used in reverse to find lower levels of abstraction, by casting it in the form “[activity] by [description]”. That typically leads to incremental or improvement ideas which are also beneficial.
Creativity Hack: Reframe A Challenge