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‘A Manager’s Introduction to AI Ethics’: Newly published chapter by Thunderbird’s Prof. Mark Esposito
Talking about the opportunities and risks ahead of us as business becomes more accustomed to using Artificial Intelligence, Alibaba’s Jack Ma said he is “quite optimistic” about AI, and it presents nothing for “street smart” people and tech leaders to be afraid of.
During a 45-minute conversation, which kicked off the World AI Conference (WAIC) in Shanghai in late August 2019, Ma focused on how machine learning can be a force for good.
“I don’t know, man, that’s like famous last words,” countered Tesla’s Elon Musk, who joined Ma on the stage. Musk shared his concerns about AI as early as 2014, when he said, “I think we should be very careful about artificial intelligence. If I had to guess at what our biggest existential threat is, it’s probably that. So we need to be very careful.”
As Tristan Green wrote on The Next Web, “mere moments into the so-called debate, we’d learned everything we needed to know. Ma was there to discuss how modern AI technology can make life better for people today. Musk was there to talk about the end of humankind.”
This discussion between two of the world’s high-profile tech moguls illustrates how early we are in the evolution of AI and how we think about the opportunities and risks that come along with it; how early we are in our understanding of the impact of AI; and how important it is for managers to have insight into the ethical as well as competitive nature of AI.
Thunderbird Professor Mark Esposito is helping to advance discussions about ethics shaping the development and use of AI and what that means in the world of global business.
Dr. Esposito, a top global thought-leader in matters relating to The Fourth Industrial Revolution, and two colleagues have contributed a chapter titled ‘A Manager’s Introduction to AI Ethics’ in a newly published book on leadership.
Key themes of ‘New Leadership in Strategy and Communication, Shifting Perspective on Innovation, Leadership, and System Design,’ published by Springer, include a new understanding about knowledge, learning, and change.
Chapter 7, ‘A Manager’s Introduction to AI Ethics,’ was written by Dr. Esposito, from Thunderbird and Hult International Business School, Cambridge, USA; Joshua Entsminger, from IE University, Segovia, Spain and Ecole des Ponts Business School, Paris, France; and Lisa Xiong, from EMLyon Business School, Lyon, France; Judge Business School at University of Cambridge, Cambridge, UK.
The book is a collaboration of today’s leading minds in leadership. An introduction by editor Nicole Pfeffermann, who specializes in new leadership and innovation communication, is followed by 24 chapters from 44 contributors.
The authors focus on how “researchers and managers need to better understand how different ideas of ethics shape how artificial intelligence can be effectively applied and leveraged as a source of competitive advantage.”
They define AI as any system designed to extract operational rules from data to inform and improve future operations. And although AI as a field will continue to evolve and AI tools in the future will look nothing like they do today, Dr. Esposito and his colleagues argue that the general dimensions of AI solutions and their potential scope of implications can be initially defined.
“A new work by Thunderbird Prof. Mark Esposito outlines four categories of problems business leaders need to understand when dealing with AI solutions: operational, design, institutional, and aggregation.” – Click to tweet
Their chapter outlines four categories of problems that managers and the businesses at large need to keep an eye on when dealing with AI solutions: operational, design, institutional, and aggregation.
These levels relate to how responsibility is distributed across AI production and use. Each category, or level, has unique ethical factors:
Operational problems – How AI is applied, the specific problem to which AI is applied and how that problem was selected.
Design problems – The decisions at this stage impact all other stages. Strategic decisions at other levels will feed back into the design stage cyclically in relation to how the update and maintenance of the system is managed.
Institutional problems – It’s important to be aware of how AI systems are applied to and informed by institutional environments, how problems are organized and defined, and whether solutions are being identified for existing frameworks or alternative frameworks.
Aggregation problems – This level concerns the adaption of AI solutions at scale and how systems with different, or competing, goals will have systemic consequences at all levels.
There are no singular solutions to ethics and AI, Dr. Esposito and his colleagues conclude. Instead, there is a need for a set of ethical principles that will help guide how to resolve and predict incidents across a variety of ethical systems.
The ethics of AI is not just a business concern and these issues should not be left to researchers and managers alone. The authors believe that a global compact on AI ethics needs to be developed and that governments need to take on a role to drive coherence of approaches in design and use of AI.
“The ethics of AI is not just a business concern and these issues should not be left to researchers and managers alone.” – Click to tweet
Far from the discussion of “Good AI-Bad AI” that Elon Musk and Jack Ma had in Shanghai, in ‘A Manager’s Introduction to AI Ethics’ Dr. Esposito and his colleagues recognize that the issues surrounding AI are complex and nuanced. And it is everyone’s responsibility to make sure they understand AI and what solutions impact in the larger AI universe.
As managers figure out how to use AI to give them a competitive edge, they need to recognize how and what it has impact on. They need to continue to shrink the divide between sustainable competitive advantages and clarity of ethical claims.
It’s clear that the authors don’t want leaders to fall into the trap of envisioning a dark future brought about by AI. They not only argue that the future is not bleak, but they also give the reader tools with which to begin to understand and take into account the complex, interconnected impact of AI solutions.
Denial or fear is not the answer to AI concerns. “AI is not a form of intelligence that can take over. It is just algorithmic computational power,” says Dr. Esposito, who also this year co-authored ‘The AI Republic: Building the Nexus Between Humans and Intelligent Automation.’
In that book, Dr. Esposito wrote, “AI’s threat to humanity has been overplayed, but that doesn’t mean it’s not a major driving force in the technology and business world that is going to irrevocably change the way we live.”