This blog is a continuation of the Building AI Leadership Brain Trust Blog Series which targets board directors and CEO’s to accelerate their duty of care to develop stronger skills and competencies in AI in order to ensure their AI programs achieve sustaining results. If you have been following this series, I have identified forty skill domains in an AI Leadership Brain Trust Framework to guide board directors and CEO’s to ensure they can develop world-class AI organizations. You can see the full roster of the forty skills in my first blog. Each of the blogs in this series explores either a group of skills or does a deep dive into one of the skill areas
This blog drills down to explain ten Emotional and Social Intelligence skills required in building an AI Leadership Brain Trust
1.) Curiosity to explore (experimentation) – No one will ever dispute that AI is a discipline that requires tremendous curiosity, as there are often multiple experiments required to test diverse data sets, using different discovery methods and algorithms to identify or correlate higher performance outcomes. However, what I have observed, over the past ten years, immersed in AI programs is that often business executives are far less tolerant to provide the exploration space that the data scientists need to investigate obscure contradictions in data, and refine their research modelling efforts. Hence, it is important that board directors and CEO’s that are striving to solve very complex problems using AI as a solutioning approach are able to handle ambiguity, the grey edges, and provide for iterative feedback to attract, develop and retain the strongest AI Data Scientists. If data scientists or AI engineers feel rushed and experience that the integrity of their research investigations are cut short or compromised, the odds are very high that your organization will experience rapid talent attrition.Building a partnering approach is key to embracing the complex and often unexpected findings that are frequently unlocked in an AI project. Key questions for CEOs and board directors to correlate in striving for increasing their AI capacity is ensuring they are measuring their organization’s innovation capacity and ensuring curiosity and trust are front and center.
Note: For more insights on curiosity, see my blog explaining in detail the importance of Curiosity in enabling AI capacity development.
2.Listening to diverse opinions and suspending judgement – One of the most challenging leadership behaviours of board directors and CEO’s is having the patience to listen to diverse opinions and to suspend judgement in AI projects. AI projects require many perspectives to get a program right. An example could be listening to diverse views like: HR’s concerns on the reactions of unions to the company’s planned use of robotics to replace human labour, to legal’s views on the employment law risks, to business leaders views on the value of robotics and the requirements to reduce costs, streamline operating processes, – all in order to remain competitive or potentially simply stay in business. Diverse views need careful consideration examining the pros and the cons at the same time, and to do this well, leaders will need skills to suspend judgement. Suspended judgment is a cognitive process and a rational state of mind in which one withholds judgments, particularly on the drawing of moral or ethical conclusions. Dr. William Isaacs, founder of the MIT Dialogue Project, uses the following example to demonstrate how we can suspend our point of view: “That is not the way I see it. My view is … Here is what has led me to see things this way. What has led you to see things differently?” This is not an easy thing to pull off. And suspending judgment requires the ability to be present and the ability to learn. Dr. Isaacs book, Presence, explores the importance of learning in that being present begins with cultivating the ability to be more alert and more acutely aware of our thoughts. Understanding what we are thinking and where our thoughts are coming from is critical if we’re ever going to let go of such thoughts, even if it’s only for a moment, and genuinely be open to another way of seeing the world. A board director and a CEO have a duty of care responsibility to ensure that their executive leaders have formal training in dialogue in order to develop skills in listening to diverse opinions and suspending judgement. Reviewing leadership development programs relevant to AI skills is an underserved learning area. Board directors and CEO’s cannot achieve world-class AI innovation leadership without ensuring their leaders increase their ability to listen to diverse opinions and to suspend judgement.
3.Openness and collaborative team orientation – As discussed prior, listening and suspending judgement enables leaders to be more open and demonstrate stronger collaborative team skills. Openness refers to the “accessibility of knowledge, technology and other resources; the transparency of action; the permeability of organizational structures; and the inclusiveness of participation.” Openness can be said to be the opposite of closed, central authority and secrecy. Collaboration means working together with one or more people to complete a common goal that benefits the team or the company. AI projects require diverse skills and talents to come together across the organization to contribute to specific tasks, ranging from data engineers who source and cleanse the data, to data scientists who design and build models to predict outcomes, to product development and solution architects who take the AI models and bridge into actionable operational processes and practices, to training and development resources who translate the new work process into specific work tasks with unified benefits with the goal to increase human confidence in new work processes to move people into sustaining activities to financial resources who define and help trace the value/benefits of the AI projects. etc. AI projects require many different skills to be engaged across functional organizational lines, and hence corporate cultures must value openness and collaborative team behaviours to master AI. Board directors and CEO’s need to ensure that they have an accurate understanding of their company’s corporate culture, and ensure that the leadership behaviours and cultural behaviours are strong in openness and collaboration, otherwise the AI program results will take longer to be achieved, or roadblocks that could have been avoided will slow down the speed of execution, due to functional divides or unaligned views. Building a digitally and AI astute culture requires investments in emotional and social skills.
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4.Inclusiveness, diversity, empathy and kindness – I put these four skills together as in my experience these skills form an integrated set of emotional intelligence behaviours that strengthen leaders willingness to listen and demonstrate authenticity in their behaviours, being genuine requires being inclusive, demonstrating diversity in all its forms, being sensitive to others emotions and being kind and considerate increases people’s willingness to give their whole self rather than selective participation. In AI, we want to bring the full human potential to bear and these four skills are foundational to being world class in AI leadership. Inclusiveness is letting people in and making them feel welcome. Making sure company leaders understand that inclusion is about ensuring that everyone’s voice is heard, opinions are considered and value to the team is evident. Diversity means that each individual is unique, and recognizing our individual differences. These can be along diverse dimensions of: race, ethnicity, gender, sexual orientation, socio-economic status, age, physical abilities, religious beliefs, political beliefs, or other ideologies. It means accepting the differences of others and inclusiveness means making people feel welcome. Emotion researchers generally define empathy as the ability to sense other people’s emotions, coupled with the ability to imagine what someone else might be thinking or feeling. “Cognitive empathy,” sometimes called “perspective taking,” refers to our ability to identify and understand other people’s emotions. Kindness defined is the quality of being friendly, generous, and considerate. Affection, gentleness, warmth, concern, and care are words that are often associated with kindness. What can board directors and CEO’s do in this area? First, ask the question: how is our talent being held accountable in demonstrating inclusivity, diversity, empathy and kindness? Is there a leadership council with genuine influence and power to ensure that the culture is creating an environment where people can feel comfortable in bringing their full selves to work? Are there clearly defined statistics of under represented group’s needs and are their support structures and resources to close the gaps? Does the organization benchmark its corporate culture – and understand the employees experiences to ensure facts are guiding policies and changes to achieve a more inclusive and diverse culture where empathy and kindness prevail? Why this is important to AI skill’s development is that you want to ensure you bring the best of your diverse talent and skills to bear in advancing AI projects. You want the whole person to show up at work, and not be marginalized in feeling their views are not listened to and that their colleagues are inclusive, demonstrate empathy and are kind. Life is short, and people have choices. Creating a strong sense of belonging is key to developing emotional and social intelligence resilience, and AI will require more diversity and suspending judgement that likely any other form of technology innovation to date. Building stronger emotional and social muscle strength will ensure your leadership foundations are advancing to world-class – and don’t under estimate how important this is to modernize your business.
5.Coaching and consultative orientation – Coaching is a process that aims to improve individual or team performance and focuses on the ‘here and now’ rather than on the distant past or future. In coaching, the coach is helping the individual or team to improve their own performance: in other words, helping them to learn and reflect. Demonstrating a consultative orientation is a discovery context where asking open ended questions, and suspending judgement, and guiding individuals or teams to learning as a result of exploring diverse questions. Board directors and CEO’s need to be alert that organizational design structures have evolved from hierarchical structures into more high performance work teams where collaboration behaviours are more revered vs command and control behaviours. Conducting a benchmark assessment of your organization’s culture in terms of emotional and social intelligence will give you clearer insight on the strengths or the blockages of knowledge flow across your organizations work processes.
6.Flexibility to work under changing conditions and contradictions – The reality with this skill /competency is everyone must be more agile and flexible to change work habits given industry dynamics. This has never been more true than in relationship to Covid-19, the global pandemic which has set some industries back ten years, while others propelled ahead to unprecedented growth levels. In terms of AI, data scientists may find their data sets are no longer valid in predicting futures, given their training data set no longer has market validity. For example in Covid-19, predictive forecasting software that was trained on year over year historical growth in B2B retail sales would not have been able to predict the rapid decline in B2B retail sales nor the accelerated growth of B2C, without human weighted adjustments in the AI model as the training data set did not have the “right context” history to learn from. Sure the AI model would adjust over time as new data was analyzed, but the sharp declines would take months and months to learn and then adjust vs a human would be able to rapidly adjust the AI model by weighting different industry sectors. Of course, if the AI model was connected to a third party economic industry growth adjustor, the AI model would self-correct rapidly, assuming the company had the foresight to ensure an economic industry GDP growth health indicator augmented the historical data set with market growth adjustments. Data Scientists need to always be alert to external market signals and be able to make adjustments in underlying data sets to ensure they remain valid under changing conditions and ensure contradictions are understood. Board directors and CEO’s can benefit from ensuring their culture and human resource practices support flexibility in terms of working from home, or in terms of recruiting talent ensuring that they value flexibility to work under constant changing market conditions. Evaluating continually culture behaviours and norms in organizations can help to monitor an organization’s flexibility to work under changing conditions and contradictions.
7. Adaptability and resilience – Having adaptability and resilience skills means you are open and willing to learn new things, take on new challenges and make adjustments to meet changes or transitions in the workplace. Adaptability and resilience skills refer to a person’s ability to adjust to changes in their environment. Being adaptable or resilient means you can respond quickly to changing ideas, responsibilities, expectations, trends, strategies and other processes at work. Adaptability and resilient people more often than not possess soft skills like: interpersonal, communication, creative thinking and problem-solving skills. Being adaptable and resilient in an AI context is very important because when you are working on projects, developing strategies and implementing different approaches to solving an AI use case, often the methods in solving a use case may need to shift from one method of AI investigation to another. It could be you are using a classification method which is very good when data variables can be easily grouped, but if data sets are fuzzy and more granular analysis is needed, a linear regression model may be best for tighter fit analysis. The best data scientists are very focused on precision accuracy and 80% prediction accuracy is not as strong as 95% prediction accuracy so the opportunity to try different methods, augment additional data sets to reduce friction or reduce false positives will always be top of mind. Board directors and CEO’s will want to ensure they have a pulse on their organizations core culture and understand how strong the adaptability and resilience is of their employee base, in particular ensuring recruiting practices seek out people that value adaptability and resilience and have experiences to demonstrate their skills in these areas.
8.Immersive learning (learning, unlearning, relearning) – AI is a field where learning and relearning is constant as immersiveness in complex datasets is a daily ritual. In AI, you can never be comfortable in knowing what you think you know as the industry is always changing rapidly, with new discoveries, methods, and toolkits daily. What used to take months, or weeks to build /or run an AI test, with todays’ agile toolkits and data processing infrastructures, models can be built on flywheels and the best models prioritized as well, so data scientists can spend their time reviewing the results and interpreting the results to advance organizational decision making. Board directors and CEO’s will want to ensure their organizations culture values learning and making mistakes as it is not uncommon in AI to have spent months or years in a particular modelling direction only to realize upon a deeper review with third party experts that the models are performing sub-optimally, and a restart from ground zero is recommended. Leaders need to appreciate the value of unlearning and relearning and ensure their AI teams are viewed as discovery scientists and many times won’t have a valid outcome to justify sustainability, while other times, they will have unlocked some new insights that will require more nurturing and investment so being patient to support a stronger learning culture is key to AI success over the long term. As a Board director or CEO, do you measure the health of your culture in terms of immersive learning attributes (learning, unlearning and relearning)? Do you celebrate failure as a recognition of continuous improvement? Creating a positive learning and nurturing environment is key to AI success.
9.Reflection and Renewal – Strong leaders know the value of R & R (reflection and renewal). They understand the importance to step back from daily operations to work on themselves. They value asking questions like “What is working well? What is not working well? What should we keep doing? or stop doing? What do we need to be more effective? AI is a field which exposes rapidly issues/gaps and values root causal analytics and developing prevention strategies. These practices leads to renewed energy, clearer focus, and increased performance of cross functional AI working teams. Many organizations are putting core values in place and creating healthy spaces and support activities for their employees, whether it’s a quiet room with relaxing music, or providing immersive water therapy treatments, like saunas, or encouraging yoga to stretch both the body and mind to operate in higher capacity levels. Board directors and CEO’s that want to build AI smart enterprises will need to appreciate that data scientists need quality quiet time to reflect on analyzing complex data sets and engage in thoughtful model design, and discovery practices. They also need to value putting in sabbatical opportunities for their AI teams and encourage their talent to continually take courses to learn. Also providing them with access to third party and peer to peer expert forums as the AI field is one which will never stand still, so recruiting talent that values life-long learning will be key to retain your data scientists. A few key questions are: Does your organization have a R&R policy ? How are you ensuring your employees specializing in AI and Data Sciences have sufficient R&R time to perform their roles successfully? Do you have a sabbatical support system in place or budget for peer to peer learning forums? How are you measuring the health of your Reflection and renewal practices? These are some of the questions that board directors and CEOs can ask to help ensure R&R practices are appreciated, and integrated into building your world-class AI enablement(s).
10.Health and Wellness – In short, health is a state of being, whereas wellness is the state of living a healthy lifestyle. Health refers to physical, mental, and social well-being; wellness aims to enhance well-being. It can affect physical, mental, and social well-being. We have all learned the importance of ensuring we have healthy employees as they will have less frequent doctor visits and be less likely to be stressed or suffer from work related injuries. Working out and eating healthy relieves stress. Having time to relieve stress during the work day can boost morale and increase productivity as well. Data scientists are known to be tied to their computers and this career path often attracts introverted profiles that are comfortable in analyzing and displaying data rather than communicating with people too much. It is very important that when recruiting data scientists that you ensure they have outside interests and hobbies and encourage them to invest in their health and wellness. Teaching your employees how to cook a balanced meal and encouraging them to live a healthy life style and provide coaching support services will go a long ways in retaining talent but more importantly keeping them healthy ensures they are more productive. As AI and advanced data scientist roles are intense often requiring strong periods for deep concentration, and applied analytical rigour, board directors and CEO’s must be vigilant on ensuring that their cultures are attune to health and wellness dynamics.
This blog discussed ten key emotional intelligence and social skills required to ensure board directors and CEO’s attracting, developing and retaining AI and data scientist talent who exhibit many of these emotional and social intelligence skills. Having well rounded AI talent that are curious, open, flexible/resilient, adaptable, value learning, reflection and renewal and practice health and wellness are key skills to ensure that your organization can achieve world-class AI competency center recognition.
To see the full AI Brain Trust Framework introduced in the first blog, reference here. Below are other key blogs on The AI Leadership Brain Trust for Board Directors and CEO’s striving to build world-class AI competency centers of excellence.
This blog introduces five emotional and social skills required for building AI leadership capacity which are: 1.) Curiosity to explore 2.) Listening to diverse opinions and suspending judgement 3.) openness and collaboration team orientation 4.) Inclusiveness, diversity, empathy and kindness, 5.) Coaching and consultative orientation.
Dec 21, 2020
This blog introduces the importance of emotional and social skills intelligence in building AI leadership capacity, and focuses on the importance of curiosity and trust building, and explores different leading researchers perspectives on diverse types of curiosity.
Nov 30, 2020
This blog continues to frame the critical need for a Board Director and CEO to build a focused AI Brain Trust and leadership program to build stronger skills to advance AI successfully. This blog continues to build the framework out on business skills, the prior three blogs were on strategic skills.
Nov 23, 2020
This third blog completes the AI Leadership Brain Trust – Strategy Framework and identifies 10 strategy skill domains, with corresponding questions for board directors and CEO’s to answer with their leadership teams and help advance sustaining the last mile of AI.
Nov 9, 2020
This blog continues to identify key leadership skills and insight questions to sustain more successful AI programs, one of the major gaps in AI programs.
If you have any ideas, please do advise as I welcome your thoughts and perspectives.
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