AI Governance and Ethics for Boards
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For enterprise leaders and their legal & compliance advisors AI Governance and Ethics for Boards 10 Things Boards Need to Know About AI 1 10 Things Boards Need to Know About AI What you will learn In the coming decades, Artificial Intelligence will bring many changes for companies, government agencies, and non-profit organizations. Business processes will be transformed by automation. Entirely new products, services, and business models will be invented. Jobs will undoubtedly be lost, but many more will be created. Education will be more important than ever and will need to become more relevant and more effective than it is today. AI will mean new competition for some and decline or even extinction for others. AI will be a key driver of economic growth and will create tremendous new wealth. Sharing that wealth equitably will be a crucial focus for policymakers and society as a whole, as will the imperative to devise sensible regulations for this powerful new technology. Board members, CEOs, entrepreneurs, together with their legal and governance advisors need to educate themselves about how to choose among AI’s strategic options, how to pursue them effectively, and how to cope with the important ethical and social challenges that AI will bring. This Microsoft AI Insight is a guide to these issues. Contents 01 06 AI will be a crucial growth driver, embrace it Build AI on a foundation of trust 02 07 Learn the basics of what AI can do Learn how to make AI fair 03 08 AI’s tactical and strategic flavors, you need both AI regulation is coming—plan for it 04 09 Understand the value of your data for AI Manage AI’s impact on jobs 05 10 Leverage AI partners, build internal AI know-how Plan for creative destruction, do the right thing AI Governance and Ethics for Boards 01 AI will be a crucial growth driver, embrace it The most important technologies are those that can solve many kinds of problems. AI is the defining business technology of the 21st century Some innovations—the automobile, the jet airplane, Artificial intelligence promises to be one of the the smartphone—are solutions to practical needs most important enabling technologies of the 21st of great economic value, such as transportation century. Over the coming decades, it will reshape and social interaction. Others—the steam engine, organizations of every size and sector, from giant the electrical grid, the PC—do not solve specific corporations to corner stores, from single-issue problems. Rather, they are enabling technologies non-profits to sprawling government agencies, from that allow the creation of new and more productive individual households to our global economic system. solutions to many different kinds of problems. Because of the endless opportunities for innovation “Microsoft has always seen itself as a builder of and business process tinkering that enabling enabling technologies.” technologies unleash, they have always been the secular engines of economic growth and social progress. At Microsoft, we have always seen ourselves as a platform company—that is, as a builder of enabling technologies for others to create value with. 3 AI can deliver $13 trillion in additional economic output by 2030 An exhaustive recent study by the McKinsey Global Institute forecasts that AI could add 16% to annual world economic output by 2030, or about $13 trillion in net additional global GDP in that year. The future is now AI is still in its infancy, just taking its first halting steps For make no mistake. Regardless of your own AI on the world economic stage. It is far from mature, strategy, you will face rivals who bet big on AI— and no one really knows what it will look like when it both existing competitors in your industry and reaches maturity, if indeed it ever does. new entrants. The more you put off your own AI acceleration, the more advantage you will cede to But for enterprise leaders weighing their options these rivals. in the present, AI strategy must be shaped by foreseeable near and medium term benefits rather The race to rebuild existing business processes and than an unknowable distant future. Betting your invent rewarding new ones with AI is not a zero-sum business on a single massive AI investment will not game. Whatever the industry, whatever the scale, AI be the right strategy for most companies (though can benefit all who invest in it. But the winnings can it will be for some). But moving without delay to only go to those who enter the race in the first place. place multiple thoughtful bets on AI with a range of possible payouts is the minimum prudent strategy that every CEO and Board should embrace. Action Item Institute an education program about AI strategy and opportunities for your Board and senior leaders. You might consider for example Microsoft’s new AI Business School, launched in partnership with Europe’s INSEAD graduate business school. The AI Business School is an online series of non-technical master classes that use written case studies and guides along with video lectures, perspectives, and talks to teach executives the essentials of AI business strategy. You may also wish to download our broader book on digital business: DIgital Transformation in the Cloud: What enterprise leaders and their legal and compliance advisors need to know. 4 © 2019 Microsoft Corporation. All rights reserved. 02 Learn the basics of what AI can do This report focuses on AI business strategy, not on AI’s technical foundations such as deep neural networks. Readers seeking a basic AI technical tutorial have a vast array of excellent and free online options to choose from. One of the best, which assumes no special background, is the series of brief online videos Neural Networks and Deep Learning by prominent Stanford AI researcher Andrew Ng. Below we provide a non-technical summary of the most important families of AI algorithms that business leaders need to know about. Artificial intelligence is not new, but its recent progress is dramatic AI is not new. At Microsoft our researchers have been working on the subject since the 1990s. But the term “artificial intelligence” is actually much older. It was coined by tanfordS computer scientist John McCarthy at a famous conference held at Dartmouth College in the summer of 1956. Bringing together a small group of brilliant pioneers that included Claude Shannon, Herbert Simon, and Marvin Minksy, the new discipline was to be based on: “…the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves. We think that a significant advance can be made in one or more of these problems if a carefully selected group of scientists work on it together for a summer.” McCarthy’s forecast that significant progress on these questions could be made in the space of a summer proved overly optimistic. The early decades of the field saw much theoretical progress but few practical breakthroughs. AI remained largely confined to academia. In the past ten years, however, the pace of progress has dramatically accelerated. AI has suddenly erupted into the business world and everyday life, with stunning new capabilities that for the first time make it genuinely useful. And more is to come. 5 Artificial intelligence still falls short of human intelligence Today’s AI surpasses human abilities in an increasing AI is also much slower to learn than humans—it number of narrow but important domains. It uses needs to see thousands of dog and cat photos to ingenious math and the awesome power of modern learn the difference between them, while a human computers to detect and exploit subtle statistical child may recognize “doggy” or “kitty” after just one patterns in great masses of digitized data, patterns example. Moreover, AI can make mistakes that are that pre-AI algorithms could not capture. But AI still obvious to us or be tricked by deceptions that would falls woefully short of our more general human ability never fool a human. to apply contextual knowledge and common sense to solve a broad range of problems that are hard to The world’s leading AI researchers say we are state in formal terms or have never been seen before. nowhere close to being able to create an Artificial AI can play the ancient games of chess and Go better General Intelligence (AGI) that can match us humans than any human who ever lived, but it still struggles in open-ended real-world intelligence. As Harvard to cope with unpredictable city traffic that the most cognitive scientist Steven Pinker puts it, it may be ordinary of human drivers master without conscious better to think of today’s AI (based largely on so- effort. called neural nets) as a kind of “idiot savant” that can perform certain specialized tasks with superhuman “AI still falls woefully short of our human skill, but does not yet understand the world in the ability to apply contextual knowledge and way that we humans do. common sense.” However restricted the scope of AI’s superhuman skills, do not underestimate what it can achieve, now and in the future. The remarkable progress in just the past five years of face and speech recognition, machine translation, and chatbots is ample proof that AI already has the power to transform business, work, and society. And this is just the beginning. Supervised learning Almost all AI applications deployed today in non- apply these labels correctly to new unlabeled examples academic settings use what’s known as supervised it has never seen before.