.

Yes, Descartes identified the two separate entities of body and mind, but he also noted that they are connected. We still use this assumption today when we say a healthy mind makes for a healthy body. But what makes for the connection? What is the glue that holds mind and body so closely aligned? In philosophical terms we may say it is the soul. The soul that gives us passion, emotions and a sense of intuitive interpretation with respect to the things we see, do and decide. As such, we may be able to replace the body and the mind, but do the ones replacing us also have the soul to make the total entity work? If body and mind cannot connect, then leadership without heart is the consequence.

      And, think about it, would you then simply comply and follow orders from an intelligent machine leader? Those who are big fans of the Star Trek movies will know the character Data. Data is a humanoid robot who is trying to learn how to understand human emotion. In one episode, Data has to take over the command of the Starship USS Enterprise. This experience turned out to be a useful lesson for both the robot and the human crew for how important human emotions are to leadership.

      Today, we have arrived in an era where this scenario may not be science fiction for too much longer. But with such futuristic views on leadership in sight, we also need to understand the kind of society and organizations we would like to see. How do we want to lead them? We need to come up with an answer to what leadership means to us and who should take up the leadership position, including assessing our own strengths and weaknesses.

      1 Reeves, M. (2015). ‘Algorithms Can Make Your Organization Self-Tuning.’ Harvard Business Review. May 13. Retrieved from: https://hbr.org/2015/05/algorithms-can-make-your-organization-self-tuning

      2 Andrews, L. (2019). ‘Public administration, public leadership and the construction of public value in the age of algorithm and big data.’ Public Administration, 97(2), 296-310.

      3 Fountaine, T., McCarthy, B., & Saleh, T. (2019). ‘Building the AI-powered Organization.’ Harvard Business Review, July-August, 2-13.

      4 Lehnis, M. (2018). ‘Can we trust AI if we don't know how it works?’ Retrieved from https://www.bbc.com/news/business-44466213

      5 Accenture (2017). ‘AI as the new UI – Accenture Tech Vision.’ Retrieved from: https://www.accenture.com/t20171005T065832Z__w__/us-en/_acnmedia/Accenture/next-gen-4/tech-vision-2017/pdf/Accenture-TV17-Trend-1.pdf

      6 Accenture (2018). ‘Realizing the full value of AI.’ Retrieved from: https://www.accenture.com/_acnmedia/pdf-77/accenture-workforce-banking-survey-report

      7 Chui, M., Henke, M., Miremadi, M. (2018). ‘Most of AI’s Business Uses Will Be in Two Areas.’ Harvard Business Review. July 20. Retrieved from: https://hbr.org/2018/07/most-of-ais-business-uses-will-be-in-two-areas

      8 McKinsey (2018). ‘Notes from the AI frontier: Applications and value of deep learning.’ Retrieved from: https://www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-ai-frontier-applications-and-value-of-deep-learning

      9 Bloomberg (2018, January 15th). ‘Alibaba's AI Outguns Humans in Reading Test.’ Retrieved from https://www.bloomberg.com/news/articles/2018-01-15/alibaba-s-ai-outgunned-humans-in-key-stanford-reading-test

      10 Gee, K. (2017). ‘In Unilever's Radical Hiring Experiment, Resumes Are Out, Algorithms Are In.’ The Wall Street Journal. Retrieved from https://www.wsj.com/articles/in-unilevers-radical-hiring-experiment-resumes-are-out-algorithms-are-in-1498478400

      11 Glaser, V. (2014). ‘Enchanted Algorithms: How Organizations Use Algorithms to Automate Decision-Making Routines.’ Academy of Management Proceedings, 2014(1), 12938.

      12 Hoffman, M., Kahn, L.B., & Li, D. (2017). ‘Discretion in hiring.’ NBER Working Paper No. 21709. Retrieved from: https://www.nber.org/papers/w21709?sy=709

      13 Son, H. (2015). ‘JP Morgan algorithm knows you’re a rogue employee before you do.’ (8 April 2015). Retrieved from: https://www.bloomberg.com/news/articles/2015-04-08/jpmorgan-algorithm-knows-you-re-a-rogue-employee-before-you-do.

      14 Hoffman, M., Kahn, L.B., & Li, D. (2017). ‘Discretion in hiring.’ NBER Working Paper No. 21709. Retrieved from: https://www.nber.org/papers/w21709?sy=709

      15 Fethi, M.D., & Fotios, P. (2010). ‘Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey.’ European Journal of Operational Research, 204(2), 189-198.

      16 Greer, S., Lodge, G., Mazzini, J., & Yanagawa, E. (2018). ‘Global Tech spending forecast: Banking edition.’ 20 March 2018. Retrieved from: https://www.celent.com/insights/929209647

      17 Paterl, V.L., Shortliffe, E.H., Stefanelli, M., Szolovits, O.P., Berthold, M.R., & Abu-Hanna, A. (2009). ‘The coming age of artificial intelligence in medicine.’ Artificial Intelligence in Medicine, 46(1), 5-17.

      18 Leachman, S.A., & Merlino, G. (2017). ‘The final frontier in cancer diagnosis.’ Nature, 542, 36.

      19 Bennett, C.C., & Hauer, K. (2013). ‘Artificial intelligence framework for simulating clinical decision-making: A Markov decision process approach.’ Artificial Intelligence in Medicine, 57(1), 9-19.

      20 Wang, D., Khosla, A., Gargeya, R., Irshad, H., & Beck, A.H. (2016). ‘Deep learning for identifying metastatic breast cancer.’ arXiv, preprint arXiv:1606.05718. Copy at http://j.mp/2o6FejM