ORGANIZATIONS CONSIST OF data. Business executives use that data to come up with the right strategies to best serve the company’s interests. As we said before, and I will repeat again: data is king!
But, what does data say? Can data speak?
Yes, on some level we could say that data speaks because, if algorithms can create transparency, then data provides useful information about what is going on. Hence, I have argued that algorithms will move into management as they will manage the data available. But, what about the other question: can the management of data to create transparency also be seen as leadership? Can data management by algorithms also lead? If this is the case, then algorithms will not only provide advice (based on the data analyzed), but also move into the role of leader, where they will make strategic decisions.
In my view, this is not very likely to happen. Why? Well, data carries information with it and, if analyzed well, we can see trends emerge. For this reason, algorithms can easily take the position of an advisor, but it becomes a different story if the information provided needs to be interpreted in line with values and priorities set by humans (and that underlie the strategy the company should take). As you all know, in our daily lives, we are raised and encouraged to have a set of values that can help us to make (difficult) decisions. In a similar vein, in organizational life, values also matter, as they help to set priorities in the projects the company engages in. It is the pursuit of those values that makes the execution of a project meaningful.
Having the feeling that what you do is meaningful is important to who we are. Meaningful experiences make our lives worthwhile and are therefore greatly valued and pursued. So, if in all areas of our life we strive to do things that make sense and can be considered meaningful, then benefits must exist which arise from those actions. One such benefit is that it makes us feels authentic. We feel close to ourselves when we see our values being represented in our actions, and therefore we truly feel like the person we would like to be. In other words, we need our decisions to be motivated by authentic goals and values, because it is those projects that we consider as important to what we do. It is those projects that feel like the real deal.
The need for this specific authentic sentiment has important implications for the question of who can and should lead in an era where algorithms are increasingly taking over the management of organizations. Indeed, at the end of the day, any decision taken by organizations where human employees are involved, should ensure that it is motivated and inspired by what feels real (from a human point of view) and not by an artificially created and directed reality. In light of this requirement, it is clear why it may not be a coincidence that when we talk about automated processing and decision making, we refer to artificial intelligence, and when we talk about human-driven processing and decision making, it may be more appropriate to refer to authentic intelligence.106
Both types of intelligence can be captured by the same abbreviation, AI, but they are not the same. Yes, both artificial and authentic intelligence can be considered to have influence within groups and organizations. However, it must be at different levels, because they clearly cannot be interpreted as having the same level of authority. In other words, artificial intelligence will be driving management, whereas leadership will need to be driven by a sense of authentic intelligence.
Why leadership needs to be the real deal
Authenticity of thought, being able to think and act in line with our values, has been considered by scholars as a key aspect of effective leadership. How so? Well, it all starts with our expectation that leaders be the agents of change.
We expect our leaders to inspire and motivate people, so that they can create value in their actions for the collective. This collective value is created if a leader can point out the direction a company must take (what to do) and explain why this is the case (introduce a compelling vision). If a leader with those abilities is in charge, he/she will be more effective in motivating and inspiring others to move in a new direction to create more and better value in the future. It is for this reason that scholars have argued that leaders need to possess transformational qualities, allowing others to be willing to collaborate to make change happen. So, the ability to transform a given situation into a new one, by means of inspiring others to follow your vision, is key to effective leadership.
Now, is the algorithm or the human best equipped to achieve such a process-based form of leadership? Academic research on transformational leadership – regarded as the prototype of effective leadership – may provide the most direct answer to this question. In fact, the initial writings on the idea of transformational leadership emphasized the importance of authenticity, if a leader wanted to be successful in motivating their followers to create value and perform better.107
Indeed, an abundance of studies have shown that leaders who act in an authentic human way, through being genuine, purpose-driven and able to connect with others, are truly transformational in their efforts. Thus, effective leadership clearly requires an authentic sense of intelligence to facilitate understanding of what really matters to people and their interests. This knowledge can, in turn, be used to motivate them to deliver value-driven change. From this point of view, the human, rather than the algorithm, seems to fit the bill. In fact, by being more specific about the process that makes leaders effective in their job, we are able to identify the limitations that are likely to prevent algorithms from assuming an effective leadership role.
Leaders influence people in value-driven ways, so the collective can benefit and long-term value can be created for all. Such kinds of influence are not achieved if leaders only present facts. Influential leaders motivate people to act and people are most likely to act if what the leader says and asks makes sense to them. They will act if what is being presented to them (the facts, a vision) is meaningful to them.
To achieve such types of influence, leaders need to be able to truly touch people’s hearts and make a human connection. Leaders thus need to know, first of all, what is happening and what changes are required to be successful. But, to make such changes happen, they need to be able to connect with their followers. Such a connection requires leaders who can communicate what is being asked by using the perspective and values that the others will recognize and endorse. In other words, leaders may know what their organization needs to do to survive or remain competitive, but the action will only be delivered if they have the skills to make it meaningful and appealing to others.
Looking ahead with a sense of purpose
Algorithms may provide information and advice on what the present business situation looks like, allowing us to infer which actions are needed, but algorithms do not possess the skills to, first, recognise what that information means to a company populated by human employees and, second, communicate in authentic ways, so that others are inspired by the message that change needs to happen. These human requirements can be easily identified when we look at the circumstances under which leaders nowadays have to perform.
What is typical of today’s business environment is its complexity, which is shaped by high levels of ambiguity and volatility. These characteristics require leaders to be agile in how they run their organization. Leaders are expected, on the one hand, to know about and adjust to the rapid changes happening and, on the other hand, be able to keep a focus on the company’s priorities. In other words, leaders need to be able to understand and use the purpose of the company to make the right strategic decisions to create long-term value.108,109
If leaders only make decisions that solely respond to updated information about changes in the market (possibly provided by algorithms), then we cannot say that the company is being led, but rather managed. A company is only being led if updated information is made sense of and responded to in terms of the purpose of the company. This means that even though an analysis may indicate that a company should make a change, a leader may reject the advised option because it does not align with company values and stakeholder interest. It is this kind of reasoning that is needed to allow leaders to connect with their employees.
Indeed, to make the required action meaningful, a leader must have the ability to understand the short-term challenges and put them into a broader perspective where the purpose of the company and the interests of all stakeholders, including employees, are accounted for. It is this ability to focus on facts and emotions, almost simultaneously, that makes a leader truly inspirational.
Can algorithms bring this human ability to the table?
Algorithms can help with the first step, which is to provide accurate updates on what the facts say and even what this means in terms of the available options. But, making the actual choice by accounting for why it is the case that the company and its employees hold certain values dear, to ensure that employees follow the direction of the leader, is a somewhat different task.
True, algorithms can make very good predictions based on the data available, but if these predictions are the only basis for the decision being made, then the decision itself is only responsive and based on short-term concerns. Effective leaders, who are able to bring the change needed to create real long-term value, are not only responsive but primarily act in pro-active ways.110 Pro-active thinking is exactly the skill that combines the power of analytics (knowing and understanding the facts) with the ability to think in the long term and in this process, to imagine the value that could be created.
Qualities such as imagination, value-based thinking and strategic vision (short term versus long term, the concerns of different stakeholders) help leaders to connect to others in ways that help them to embrace the change requested. Indeed, deciding to follow a leader in often uncertain circumstances takes people out of their comfort zone and brings emotions, such as fear and anxiety, into the picture.
Leaders need to have the skill to show empathy and recognize the fact that followers will experience those emotions. Therefore, leaders need to be able to nurture their followers into staying motivated and engaged. For this to be successful, leaders are required to be intuitively attuned to these emotion-based dynamics.111,112
Our own research shows that we do not believe that algorithms can possess these abilities.113 In one study, we asked participants to evaluate the qualities of a human versus an algorithm, to understand the meaning of relationships between humans. Not surprisingly, our results revealed that humans were judged to be more intuitive, as well as better able to understand the perspective of another person and act upon it accordingly. Algorithms, on the other hand, were judged to be less qualified when it came down to these skills, mainly because they are seen as rational decision-makers with no sense of intuition.
It’s all about connecting with others, stupid!
These findings support the message that algorithms cannot connect with humans in the way another human can. Connecting with humans requires the ability to install a somewhat authentic feeling that emotions are understood and values shared. Algorithms lack these social skills and, as such, emphasize the reality that they are non-human and thus cannot act in authentic ways. Though this conclusion is a simple one, it carries important implications for the ability of algorithms to ever take up a leadership position.
Effective leadership materializes only if the kind of influence achieved allows others to follow. True leadership, in its essence, requires the ability to connect with those who are expected to follow. The fact that algorithms do not possess such abilities, nor are perceived to have those abilities, makes them incapable of leadership. Even more so, it makes thinking about leadership by algorithm, leadership that would be responsible for the interests of its human followers, a scary idea to many.
Being responsible for others indicates that one is judged as morally capable to evaluate and understand the interests of those you are leading. You need to have a sense of intuition that is morally-laden, if you want to lead. Academic research shows that we do not attribute these qualities to machines in leadership roles because we do not regard them as having a complete mind.114 You may wonder now, what makes for a complete mind?
To understand this, let’s take a look at how research defines the human mind when it comes down to morality. As I mentioned briefly earlier, a range of studies has revealed evidence that in our perception, a human mind entails the two dimensions of agency and experience.115,116,117,118,119,120 Agency is the capacity to do, to plan and exert self-control; whereas experience is the capacity to feel and make sense of things.
Algorithms may be attributed some agency, although this is still an issue where no consensus has been reached. For example, the EU recently published ethical guidelines for a trustworthy AI which was criticized because people believed that AI cannot be trustworthy. The reason for this claim was that AI is considered not to have agency. My own research on trust would suggest that this is not entirely true because we do seem to be comfortable with trusting algorithms to do what they can do best, that is, to be rational and deliver fast accurate analysis.121 In this sense, algorithms can be seen as reliable, but this is not the same as being trustworthy. Being trustworthy also involves acting with integrity and being aware of the interests of others. (For more insights on what building a trustworthy image entails, see chapter nine.)
One thing that is, however, clear for the algorithms that we have developed today is that they do not possess the benefit of experience. And because algorithms are not attributed with both dimensions, humans feel uncomfortable letting algorithms make decisions that have consequences for the interests of different stakeholders. Only a leader who possesses authentic, human, mental capacities is expected to be able to do this.
Failure happens; what matters is, can we correct it?
Does all of this mean that humans, relative to algorithm, are flawless when it comes to taking care of the interests of others? Of course not! We know all too well that humans make moral mis-judgements and show unethical behaviors. But, contrary to algorithms, we perceive and accept that humans do possess both agency and experience. And because we perceive humans to have these abilities, we also trust them more than algorithms to correct misbehavior. Algorithms do not have the ability to authentically feel and experience what others go through when being treated badly, or when their interests are violated and forgotten about. Even more so, their inability to take the perspective of others makes them unable to make decisions on behalf of others and, as such, are perceived as incapable of leadership.
Let us consider again Amazon’s experiment to use an algorithm to automate their recruitment process. This case taught us that the employed algorithm duplicated the human bias to favor men over women for the specific software development jobs they were advertising. As I just mentioned, it is not just algorithms, but humans too, that make such biased judgments. The difference is that humans are aware of the social consequences that emerge from the employment of this biased practice. The important question here would therefore be whether algorithms could sense the dangers associated with these consequences. Clearly, they did not. The algorithm did not say, ‘wait a minute, is the outcome of my decision what we would like to see in the company and hence society?’ Not at all. It took human intervention to change the selection process.
This example makes it clear that if we decide to make ourselves dependent on automated technology to lead our organizations, we would almost certainly face consequences that would be difficult for humans to accept. Algorithms can make data transparent and even provide advice, but it cannot be allowed to take charge of the decision-making process.
All of this signals that algorithms can be used to manage the execution of our (value-driven) directives, but not create such directives. If we employ algorithms in this way, it will mean that humans are better able to direct their attention towards more complex, higher-level responsibilities. Workplace culture, as a result, will be better able to foster moral awareness, creativity and innovation. And at the end of the day, isn’t this what leadership should really be about?
Does it make any sense?
The verdict seems ready: leadership in today’s world, and especially so in the future, needs to be driven by an authentic human sense of intelligence to be effective. If we want to follow up on that advice, we also need to know what dimensions this kind of intelligence includes. In other words, which unique skills do humans bring to the table to make them the undisputed business leader of tomorrow?
If there is one aspect that addresses the core functions that business leaders will need to fulfil in the future, then it involves sense-making. Organizations today and in the future will face very complex situations, combined with a volatile market that requires leaders to make decisions quickly and accurately. To do this, it is necessary that sense can be made of the organization’s goals, as well as why (its purpose) and how they can be achieved within a business environment characterized by these unique features.
Leaders help define the organizations they lead. Therefore, those same leaders need to make sense of what they are doing and more importantly, why they are doing it. This helps employees to make sense of very complex situations for which no formal rules (yet) exist. We all know that once things become complicated and more difficult to cope with, we look in the direction of the authority to guide us. We did so when we were children, and we do the same at work. Humans have the innate need to look for help from their leaders when things get tough. This reality clearly emphasizes that leadership is more about responsibility than many assume, hence, making moral awareness an imperative. Unfortunately, too many times we hear about leaders thinking about their job more in terms of what they are entitled to, rather than recognising the responsibilities that come along with their leadership position.122
Leaders can and should provide guidance to others, but it very much requires them to have the ability to create meaning for those who they lead. For this reason, the ability of sense-making has to be recognized as an important quality for the leader of tomorrow. The ability to make sense corresponds to the specific intrinsic desires that make us human and, in this way, sense-making adds value to our lives. What unique human skills make up for this general ability to make sense of things? What skills can be located within the human brain with its 200bn neurons, connected by 10,000 synapses, which is impossible to replicate even with today’s technology?123
Unravelling complex situations so that they make sense to others implies an equally complex working of our brain. It implies that leaders need to be able to bring different perspectives to the table, understand the meaning of those perspectives to the stakeholders involved, and are both creative and integrative in producing a solution that creates most value (not only in financial terms but also in terms of purpose fulfilment).
This complex interplay of abilities represents an image of the human skill-set that aligns well with the skills that the World Economic Forum (2016) identified as being needed to deal with the technological revolution that we witness today. Specifically, their Future of Jobs Report emphasized that humans in the near future need to be able to solve complex problems, engage in critical thinking, act creatively and be equipped to manage people.
On the fabric of sense-making
It is the interplay between abilities that creates sense-making value, which only humans can deliver in a leadership role. Put together, these abilities form the skill set required for future leadership to succeed. But why are these abilities so important?
To understand their unique value to the leadership of tomorrow, we need to understand the psychological fabric that makes up for the sense-making ability of a leader. This fabric consists of a number of well-defined abilities. How does each ability work in making a leader more effective? Understanding the specific abilities that are seen as important to the overall skill of creating meaning are obviously important in order to develop more effective training and coaching of our future leaders. So, where do we start? What is important to realize first is that these abilities are not all operating at the same psychological dimension. Specifically, each ability is a combination of a desire to create meaning (motivation), to be able to think about it (cognition) and to realize how it makes people feel (emotion).
The existence of these psychological dimensions already distinguishes humans from algorithms in terms of the complexity of their behaviors. Indeed, as I discussed earlier (see chapter one, the Turing test), algorithms arrive at their decisions (and hence behavioral displays) in a less complex way. They only reason in one specific manner, which is learning based on what they observe. In other words, algorithms learn and subsequently model the behavioral trends that they identify in the data they analyze.
For example, the chip-maker Nvidia recently introduced an experimental vehicle based on an algorithm that had taught itself to drive by observing how humans drive. Thus, the algorithm learned through behavioral observation and subsequently modelled the most consistent behaviors. Yet the algorithm did not engage in any reflective, motivational or emotional analysis of what driving means for the drivers.
As the Nvidia example demonstrates, algorithms are not able to think at a deeper level, where motivations and emotions are integrated with a cognitive analysis to make sense of things. An algorithm’s way of learning is thus less complex when compared to the complex interplay between neurons and synapses in the human brain. Therefore, their resulting actions and decisions can be considered straightforward and rational, as it is based on principles of consistency and replicability.
If there is one thing that effective leaders know, it is that every individual is unique yet desires to be affiliated with and treated in the same way as others. This complexity requires leaders to integrate emotions, motivations and cognitions into their judgments and act accordingly. It is exactly this kind of thinking that we need to see present in leaders in the 21st century. Such a conclusion implies that leaders of the future require the human touch that can bring to the table the abilities of critical thinking, curiosity, agility, imagination, creativity, ethical judgments, emotional intelligence and empathy.
Figure 1 illustrates how a leader’s crucial skill of sense-making is derived from a diverse set of abilities that operate on multiple psychological levels (motivation, cognition and emotion). Below, I discuss each ability in greater detail.
Figure 1: Abilities driving the skill of sense-making as required for leaders of the future
Critical thinking
When confronted with complex situations, it is necessary to identify where the opportunities for your company lie. Where does your focus need to be in this complexity? What kind of information do we want to use and which can we ignore?
Obviously, algorithms can help here as they gather and analyze data faster than any human. They are the masters of managing complex information! So, it is only justified that we use them in this way. However, there is so much more about data that needs to be considered. What purpose are we striving for and what kind of data is needed to inform us about the opportunities we can create to achieve that goal?
Algorithms run on calculative principles, so humans need to assign weight to what matters more, versus less, to help categorize and bring structure to the data. It is the ultimate goal that gives meaning to the data search and subsequent analytical process as conducted by the algorithm. We therefore need leadership to be able to reflect and consider this critical issue. But this is not where critical thinking ends.
Once the relevant data is identified, we also need to analyze it in terms of the strategy that we need to develop, based on the demands imposed by the business environment. So, we may have our purpose and our own view of reality, but there is also a reality out there with its own specific demands. You need to take the latter reality into account too if your company is to survive in the long term.
All of this requires leaders to be able to think outside of the scope of the provided data and make connections others (i.e. competitors) may not see. It also requires the ability to think logically to evaluate how the results (as achieved in a competitive and demanding market) relate to what you want to achieve and why. This logical component of thinking is essential, because not every successful business scenario is necessarily the right one. The ultimate business scenario at the end of the day is the one that optimizes the achievement of your purpose. Not every company is in business for the same reason, so they are not necessarily focused on creating the same kind of value. Algorithms lacking the emotional connection with what brings value to people’s lives do not engage in this kind of analysis.
Finally, critical thinking skills are not only necessary for leaders to use, but also to install in the company’s work culture. Leaders build work cultures by setting examples and instilling values for which the company wants to be recognised. In this sense, a leader who practices critical thinking will also equip their followers with the same skill. After all, as we will see later, employees will work with algorithms to optimize efficiency in the operations and execution of tasks, so they need to be able to manage these processes in the same way that the leader manages the direction and purpose of the company.
Curiosity
Your ability to think critically is linked to another human (cognitive) drive, which is called curiosity. Curiosity is one of the new buzz words in management today. In fact, curiosity is a leadership skill that many business leaders are starting to consider a key quality in today’s volatile business environment. Why would that be the case?
Dan Shapero, vice president of Global Solutions and head of sales for LinkedIn, put it succinctly in an interview when he said, “Leaders need to understand and interpret the massive amounts of data that are coming at them every minute of every day and be able to cut through the noise … We have to be able to ask questions that focus on what this all means for our business, our customers, and our teams. This puts a premium on having people who are driven by a sense of curiosity.”124
And, indeed, organizations driven by a curious attitude perform better. Curiosity is a strong predictor of employee performance and, in combination with the skill of critical thinking, becomes a powerful (human) weapon in producing valuable outcomes for the company. What is important to note is that research shows that it is curiosity in general that makes people successful and not simply a sense of curiosity in a specific task.
In his book Originals, Adam Grant, professor at the Wharton School of the University of Pennsylvania, elaborates on this general/specific issue by pointing out that Nobel prize winners have a greater sense of curiosity beyond their own field of expertise than scientists who are less accomplished. The study he refers to looked at every Nobel prize-winning scientist from 1901 to 2005 and examined their hobbies and ways of expressing themselves creatively. The surprising result was that scientists who showed great engagement in hobbies like art, music and so forth, had 22 times more chance of winning a Nobel prize.
What do these results really suggest? Well, these findings underscore the observation that it is really a general level of curiosity that determines the success of a person, rather than curiosity in a specific area of expertise. This general sense of curiosity brings a more critical and refined way of looking at what happens around you to the table. It is especially this kind of attitude that allows curious people to think beyond what they see and come up with more creative solutions.
Without curiosity, leaders are less likely to get better at what they do and will be deprived of useful information that can help them grow and improve the effectiveness of their organization. According to the Cambridge dictionary, curiosity is defined as an eagerness to learn about something. Being curious promotes learning and motivates people to improve themselves in many dimensions of life (both professional and personal).
Why does it improve learning? Curiosity pushes people to think outside of the box. It makes them attentive to the fact that there is more than one solution for a problem. A wider range of solutions exists! This awareness motivates people to look for new possibilities, to explore different ways of approaching decisions and to challenge beliefs that they have held for a long time. Curiosity is the primary challenge to status-quo thinking. It is not expected to be part of the manager’s job (see chapter four), but should definitely be considered a part of a leader’s job!
The judgment of the jury in this is clear: curiosity helps people grow, encourages them to learn new things and enables them to develop into more creative decision makers. Curiosity is a motivational driver that comes from within the individual. This implies that to develop this ability, you have to make it happen yourself. No one else can really do this for you. We all know that dealing with complex and uncertain situations creates a tension within people that makes them feel uncomfortable. Depending on the way we regulate this tension, we may either grow and perform better, or become paralyzed and stick to the status quo. The one feature that decides whether you end up in the former situation and not the latter is curiosity.
Why? Being curious implies that you realize you do not know everything. Fortunately, though, you also realize that there are plenty of opportunities around to learn; it depends on you whether you take those opportunities or not. It is in this explorative process that you are likely to find a solution that fits with who you are, what you feel comfortable with, and which will allow you to grow. Having an open mindset and being curious about how things can be done differently brings with it the power of imagination, which fuels new and creative ways of dealing with business challenges. Being both curious and critical in your thinking creates leadership that acts in agile ways.
Agility
It is no surprise that a famous business rule is that the only thing unchanged is change itself. Indeed, in today’s business environment, situations can change quickly. And with this change comes different expectations and demands. Organizations need to adapt quickly, but without losing sight of the goals and purpose they wish to achieve. No organization is helping themselves if they only follow what others do and in essence become a purposeless company. To avoid this fate, agile leadership is needed. Leaders are required to improvise and find new ways of acting quickly. This, in turn, requires strategic thinking, which allows an organization to remain on course to achieve its goals while at the same time being attentive to the new business requirements.
Agility is typically a human quality that algorithms do not possess. Great examples of the limited ability of algorithms to be agile can be found in the gaming industry. We can make algorithms learn the ability to play a video game like StarCraft II up to the level that they beat the best human professional players. But, if we change just one parameter in the game, the algorithm has difficulties adapting immediately and will lose again. Algorithms cannot step out of one situation and into another unfamiliar one. Because of the fluid business environment, organizations face these types of changes frequently and so would not be able to survive without agile leadership.
Agility requires (like curiosity) an open-minded approach which quickly recognizes that the old ways will not work anymore, so new solutions need to be found. To find those solutions, agility is required. Agile leaders are able to take different perspectives towards the changes they are facing and, combined with a sense of curiosity, are energized to find an alternative approach that will resolve the challenge faced.
Taking different perspectives implies that leaders have a sense of imagination and can see new ways of working that do not yet exist. Leaders therefore need to be curious and adopt different perspectives simultaneously, which is encouraged by having a strong sense of imagination. To make things even more complicated, all of this has to operate in a quick and seamless way. To achieve such a state of mind, leaders are required to train themselves in taking different perspectives and adopt a reflective (where multiple options are considered) and integrative style (where the different perspectives are integrated to reveal one solution that is considered optimal given the situation).
Imagination
Fluctuating business conditions induces the need to work in new and different ways. At the same time, you cannot change the values that underlie your drive for performance, so you adapt but without compromising your values. What makes this process so complex and difficult to attain is that it requires decision making and action that basically does not exist yet. It requires the ability to mentally simulate the probable success of adopting new business models and strategies. This distinctive ability concerns the power of imagination and is an ability most required when something you are looking for is invisible or does not yet exist.
To engage in mental simulations, you need to have the right set of abilities. Indeed, you need to understand how the game has changed (critical thinking); stimulate yourself to look for new solutions (curiosity and agility); and combine the information you already have with the additional information you need to successfully deal with the new challenge. This latter aspect of combining what you know with the things you do not yet know is the ability to imagine different realities.
In its essence, imagination is the dynamic process of filling up the gaps, i.e. the gaps that exist in-between the pieces of information you have at your disposal need to be filled up by other new data to construct a more comprehensive and different way of working.125 What is important to understand is that this imagination process implies that in order to find the new information, you will have to look outside the framework that you have always been using. When both types of information (the known and the unknown) are put together, it needs to be done in such a way that it is not a simple extension of your old ways of working! Instead, it needs to reveal a new and different way of operating that fits the changed reality that now confronts you. In this sense, 1 + 1 = 3. The process of imagination and how to stimulate it is receiving increasingly more attention because, for obvious reasons, it is one of the primary determinants of creativity.126 As the American Heritage Dictionary mentions: imagination can improve the ability to “deal with reality by using the creative power of the mind”.
Creativity
Can you be creative without imagination? Not really. For most of us, imagining different realities is a fun activity. When we experience stress, we often retreat to our own imaginary worlds and think about alternate realities that make us happy. Humans have this unique ability to entertain themselves in the world we call imagination. This ability, which distinguishes us from algorithms, is very important when it comes to creativity. As Einstein once said, “creativity is intelligence having fun”, and all of us understand immediately what he meant by this quote. Algorithms cannot be creative because they work with pattern recognition and curve fitting, which does not allow for the exploration of a reality that does not exist. It thus seems unlikely that algorithms have the same ability as humans to solve creative problems.
Creativity is a process that requires imagination. As creativity involves coming up with new ideas and solutions, imagination is required to, first of all, develop different ways of looking at reality. In those different perspectives, we try to identify opportunities that can generate novel solutions to problems. Creativity is therefore regarded as a key enabler of tremendous advances in organizational productivity and economic growth.127 However, creativity does not only produce novel solutions, but also ones that are useful, which is vital for organizations in the context of a fast-paced business environment.128 The fact that creative solutions also need to be useful is important to stress in light of the human ability to make sense of things.
Creative solutions are meant to solve problems that hinder the pursuit of our goals and achieve results that we consider appropriate in light of our purpose. Because creative solutions are so closely aligned with the value that we want to create as humans, the aha moment that precedes the creative idea is felt physically, emotionally, and mentally. Creativity in itself is such a deep and authentic experience that the process does not function within a controlled and structured operational mode. Algorithms – in their effort to model the human brain – function on a set of well-defined calculative principles. Their way of working is modelled after insights from the field of computationalism, which simplifies the workings of the human brain and associated thinking process to some arbitrary act.129 This kind of algorithmic formalism does not leave room for chaos and, as such, does not allow for any expression of the human experience of creativity.
Does this mean that algorithms cannot provide any input to the process of creativity? Not at all. If we look at scientific literature, we see that creativity can be reached via two paths: flexibility and persistence.130 Flexibility is associated with an open mindset that helps people to adopt different perspectives; avoid being pinned down in looking at reality in a fixed stereotypical way; and connect unrelated concepts and ideas. Persistence is more structured and includes diligent work, systematic thinking and exploration, and knowledge-building in an incremental linear manner.
Looking at these processes shows some parallels between what humans and algorithms can do. Algorithms are rational data processors that systematically work through massive amounts of data, as well as generate transparent and consistent pieces of information – a way of working that fits well with the notion of persistence. Algorithms are persistent (and fast!) in processing data. Humans, on the other hand, possess the ability to be more chaotic, blend in emotions with their thinking and deviate from a systematic and consistent way of working. These are all abilities that make thinking less fixed and more flexible.
What do these scientific insights teach us? First, the definition of creativity makes clear that a creative outcome ultimately depends on the notion of flexibility, because a creative solution needs to be something new. As such, truly creative solutions will always require human input. It also means that algorithms, because of their persistence, can assist the creativity process by helping to gather and make data more transparent. This, in turn, will provide humans with the necessary input to unleash their chaotic and unpredictable processing mode.131
Emotional intelligence
Anyone who has been in a leadership role knows that your decisions impact others, as well as yourself, on many levels. In the last decade or so, calls have become very loud for organizations and their leaders to become better at nurturing employees and showing some empathy. For leaders, this includes taking care of both their own emotions as well as those of others. This implies that leaders should be able to recognize emotional disturbances. This ability to recognize emotions (both in themselves and others) and manage them to reveal a positive impact is called Emotional Intelligence (EI).132
In line with this call towards nurturing emotions within the organizational setting, it has been estimated that demand for EI skills will increase by a factor of six in the next few years.133 The world has clearly woken up to the fact that our business environment creates stressful lives. Although the awareness seems to be there, organizations have not always been responsive enough in terms of fostering the ability to develop and use EI. This may be considered surprising, because EI has many positive influences in the workplace.
Research reveals that employees with high EI are consistently rated as more dedicated to their job, better performers and easier to deal with.134 These findings underscore the idea that EI is a valued social skill because it facilitates how you interact with others in the most optimal and beneficial ways. Indeed, EI can help you to understand others, take different perspectives and regulate your social interactions with others. Those who have a high level of EI have a high sense of self-awareness (they know their strengths and weaknesses). They are also able to recognize their emotions and manage them (e.g. use fear in a motivating, rather than a destructive, way). Individuals with a high EI can thus put their emotions into perspective and use this ability as a strength to help them be more effective and perform better.
If algorithms will be the new co-workers, then we need to be able to collaborate with them. EI is an ability that many technology companies hope to integrate within AI. Indeed, new technologies will gradually automate more routine tasks and eventually make the leap to decision making within the context of managerial responsibilities.
If an emotional AI can be achieved, leadership may become automated after all. In light of these predicted developments, having algorithms equipped with some kind of EI ability will likely transform the future work setting, making it even more effective. In addition, because many jobs will increasingly become automated, employees will, in a way, be forced to re-discover their ability to connect with other people.
Indeed, as algorithms take over the more analytical jobs, humans will be more in demand for jobs that deal with other humans. For example, in the financial sector, banks are gradually replacing human employees, particularly those with jobs that are largely mechanical and calculative, with algorithms. This is an obvious trend, because now AI is rapidly advancing, thinking tasks that require analyzing and processing data can be easily automated. It makes sense then, that some bankers today will proudly state that they are not banks anymore, but rather technology companies with a banking license. This development creates a reality where human employees have to start focusing on the tasks that algorithms are not able to do, those jobs where social and emotional skills are a priority: the feeling tasks.135
This shift in focus for humans is seen more and more in job advertisements, where banks will emphasize the need for employees to have strongly developed social skills. In fact, some of our own research suggests that wealthy clients in particular seem to demand more face-to-face interaction the more automation kicks in. As such, relationship management will become a crucial job within the financial industry. In a similar vein, management of the work force will require people managers. This is not such a surprise, because within such a tech-driven environment, it is actually quite a normal human response for both employees and customers to need more social contact.
So, both algorithms and humans will engage in their fair share of jobs, but, at the end of the day, they will have to collaborate to create value. From this perspective, developing algorithms able to deal with the emotions of customers and employees would be highly beneficial to organizations. However, if we look at the current state of affairs, then it is fair to say that machines cannot recognize human emotions beyond the surface level. They may recognize an emotion, but they do not have the qualities to understand what the person expressing this emotion is really feeling and what this means. At the same time, research has revealed that algorithms cannot feel authentic emotions, limiting them to make sense of those of others in a way that signifies real understanding.136 Put differently, at this moment in time, developing algorithms equipped with EI is not possible. Hence, algorithms and machines cannot be attributed human qualities, especially not those needed to lead people in appropriate, respectful and empathizing ways.
Empathy
EI implies the skill of emotional recognition. But why would you need to be able to recognize emotional states? Well, to connect with others and develop relationships with them. So, is EI sufficient for the relationship to happen? Not entirely. We need something more. Specifically, we also need the deeper-level ability of being empathetic. Empathy is the capacity to understand the implications of the emotions people experience. What is it that people are feeling behind their emotional expressions? Why does someone experience these emotions? Showing empathy helps to develop a better understanding of who the other person is, and the kind of joy and pain they may experience.
Empathy is believed to be uniquely human, as it helps us to accept another person with the emotional weaknesses and strengths that they display. Algorithms, on the other hand, run on well-defined calculative principles aimed to optimize outcomes, which means that their functioning does not need the ability to dig deeper than the surface of the data that is available. As such, algorithms do not have the ability to engage in the process of obtaining a deeper understanding of the external environment, let alone accept that environment.
This limitation is nicely reflected in comments by Bill Mark, president of information and computing services at SRI International, whose AI team invented Siri: “We don’t understand all that much about emotions to begin with, and we’re very far from having computers that really understand that. I think we’re even farther away from achieving artificial empathy.” Of course, if empathy cannot exist between human and algorithm, then it is difficult to talk about the possibility of developing trusting partnerships. After all, empathy would involve mutual recognition of one’s feelings, which would lead to the existence of mutual trust where both parties can genuinely take care of each other.
Ethical judgment
The use of algorithms has clear financial benefits, as they cut costs dramatically. Of course, this will only be the case if algorithms are used in ways that suit their abilities. Replicating routine tasks, being consistent and predictable, and interpreting data, for example, are all fine. But, organizations have to make many decisions that are more complex and involve the ability to be sensitive to the interests and values of other stakeholders.
In this sense, many business decisions need to be evaluated in light of upholding important ethical values. Indeed, business leaders need to be aware of possible ethical dilemmas inherent in business decisions and possess the ability to judge how to deal with it. Specifically, to make the morally right decision requires the leader to make an ethical judgment. This is where algorithms fail, and humans bring their unique abilities to the table. Because algorithms lack empathy, humans consider them to not possess the full range of human qualities and are thus limited in their ability to make moral choices.137
Consider the following thought. In theory, it is the case that any machine can be fed a set of ethical principles outlining a clearly defined set of values and operate on those values. But, what does this set of values really mean to an algorithm? Can algorithms understand the meaning of a value to people, to organizations or to society at large? It is not always easy for humans to grasp the real meaning of values and incorporate them into their behavioral repertoire. So, how easy would it be for algorithms that lack empathy to understand the meaning behind those values? How can an algorithm decide what a universal right is to humans if it cannot imagine and feel what such a reality actually means?
Algorithms can learn and scrape the internet to see how people look at ethics and apply it in their lives. However, these efforts remain abstract and do not allow for an algorithm to grasp the meaning of why people value ethics. So, they can scrape ethical values, but not grasp ethical meaning! What can we learn from this thought exercise? Well, no matter how powerful an algorithm is in dealing with all the data available, it doesn’t change the fact that all technology is neutral. It does not feel, shows no empathy and cannot understand the meaning of a moral decision to the different stakeholders involved in business decisions.
So, algorithms lack the ability to arrive at ethical judgments and are therefore considered unfit to make leadership decisions. Furthermore, because morality is an authentic feeling unique to humans and our society, people only consider human ethical judgments to be legitimate. In fact, recent research shows that people consider algorithms (as compared to humans) to exhibit less moral authenticity.138
What makes humans then so much more suitable to make these moral decisions? Compared to algorithms, humans are equipped with a sense of moral awareness. Moral awareness can be considered the innate level of sensitivity and responsiveness that humans possess to recognize that a given situation has a moral component.139 To have this kind of awareness, one needs to be aware of the needs and goals of all the stakeholders involved to delineate whether a conflict of interest exists.
For obvious reasons, such a sense of awareness requires complex and integrated reasoning that algorithms are not able to achieve. Having a sense of moral awareness is critical for engaging in ethical analysis, judgments and finally conduct.140 Indeed, we know from research that ethical judgments guide ethical intentions and behaviors.141 And, it is this link between the ability to engage in ethical thinking, and to act in line with the corresponding ethical judgments, that makes it so unique and separates what we can find in a human from what we do not find in an algorithmic leader.
Leaders with the ability to think through the ethics of a situation are better equipped to make sense of a situation. By being able to recognize the ethical requirements of a situation, the meaning of that situation becomes clear and the appropriate response becomes apparent. Leaders with this ability do so by explaining the ethics of the situation, what the expectations are and how one should behave.142 By conveying ethical expectations, leaders do what they are supposed to do: they guide their followers and encourage them to pursue the company values.
All of this makes clear that the moral complexity that comes along with doing business does not translate easily into the workings of an algorithm. To put it briefly, based on what we have seen so far, two important problems arise. The first problem is that multiple philosophical perspectives of ethics (e.g. justice, relativism, egoism, utilitarianism, and deontology) exist, which influence an individual’s ethical judgments. This reality indicates that humans themselves differ among each other in terms of how they define ethics. This also means that some people will, for example, consider lying as something that should never be allowed, whereas, for others, lying is acceptable if it helps to avoid harm to others. Why is this a problem for the possible ethical development of algorithms?
Well, let’s assume that we want to develop an automated work place where algorithms act in consistent ways across locations; such a set up requires that algorithms define ethics in similar ways. So, ultimately, for algorithms to achieve this developmental stage, humans would need to reach a consensus on how to define ethics first. To complicate things even more, the second problem is that, because algorithms cannot feel empathy, they fail to be morally aware. Thus, algorithms lack the ability to arrive at ethical judgments and make decisions in situations where multiple stakeholders are involved.
Given all these constraints that prevent algorithms from making ethical judgments, we are confronted with a new problem. Now that organizations are showing a commitment to creating strong, automated work environments, how can we be assured of the presence of an ethical compass guiding this automation trend? It is clear that the most adequate response will be to have human leadership in place to assess the ethical standards of any automation effort from a human-centric perspective.
Are companies aware of this need? They are. This awareness is obviously being helped by the fact that when it comes down to the development of algorithms to make decisions, the law is lagging behind and regulations cannot keep up. As such, it is hard to avoid the idea that one should not simply focus on compliance, but more so on having leadership in place that builds a culture of doing the right thing. Why wait for regulators to catch up with technology development, if leadership can also model the right kind of behavior?
Because of this awareness, it is no surprise to learn that in a Deloitte survey of 1,500 US executives, it was found that 32% of organizations considered ethics a top priority. But, although some awareness seems to exist, few companies have developed procedures to bring ethics training to life in the management of AI. So, more work is needed there.
The companies that do act on this challenge, however, approach it in a specific way. For example, companies like Microsoft, KPMG and Google, create internal positions that guide the use of algorithms within the company context. The senior leaders placed in these positions work with ethics frameworks to supervise how the technology is used in both efficient and ethical ways. These positions are now being called AI ethicists.143 The company KPMG identified this position as one of the top five positions needed to succeed in 2019.144,145 They stated: “As ethical and social implications of AI continue to unfold, companies may need to create new jobs tasked with the critical responsibility of establishing AI frameworks that uphold company standards and codes of ethics. Initially, these roles could be fulfilled by existing leaders in an organization, but as the effects of AI fully take shape, it may need to be the responsibility of one person to ensure these guidelines are upheld.”
Conclusion
With all these unique human abilities present and ready to be developed further, it is safe to say that the art of leadership will not change that much. It will remain human. Yet, it must also be stressed that the automation trend is not to be reversed. So, the question of how to use technology and for what purpose will only become more important. When this happens, leaders will need to be able to make decisions based on the data delivered by automated management, but with a clear sense of consciousness, responsibility and sense-making.
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