François Candelon

Rodolphe Charme di Carlo

Midas De Bondt

Theodoros Evgeniou

<article-ideainbrief class="article-ideainbrief">
 <h4 class="ideainbrief-title">Idea in Brief</h4>
 <div class="ideainbrief-contents">
  <h5>The Challenge</h5>
  <p>As companies increasingly embed artificial intelligence in their products, processes, and decision-making, the focus of discussions about digital risk is shifting to what the software does with the data.</p>
  <h5>Why Is This a Problem?</h5>
  <p>Misapplied and unregulated AI may lead to unfair outcomes, primarily because it can amplify biases in data. And algorithms often defy easy explanation, which is complicated by the fact that they change and adapt as more data comes in.</p>
  <h5>How to Fix It</h5>
  <p>Business leaders need to explicitly examine a number of factors. To ensure equitable decisions, they need to evaluate the impact of unfair outcomes, the scope of decisions taken, operational complexity, and their organizations’ governance capabilities. In setting standards for transparency, they must look at the level of explanation required and the trade-offs involved. In controlling the evolvability of AI, they need to consider risks, complexity, and the interaction between AI and humans.</p>
 </div>
</article-ideainbrief><p>For most of the past decade, public concerns about digital technology have focused on the potential abuse of personal data. People were uncomfortable with the way companies could track their movements online, often gathering credit card numbers, addresses, and other critical information. They found it creepy to be followed around the web by ads that had clearly been triggered by their idle searches, and they worried about identity theft and fraud.</p>

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<p>For years public concern about technological risk has focused on the misuse of personal data. But as firms embed more and more artificial intelligence in products and processes, attention is shifting to the potential for bad or biased decisions by algorithms&#8212;particularly the complex, evolving kind that diagnose cancers, drive cars, or approve loans. Inevitably, many governments will feel regulation is essential to protect consumers from that risk.</p>
<p>This article explains the moves regulators are most likely to make and the three main challenges businesses need to consider as they adopt and integrate AI. The first is ensuring fairness. That requires evaluating the impact of AI outcomes on people&#8217;s lives, whether decisions are mechanical or subjective, and how equitably the AI operates across varying markets. The second is transparency. Regulators are very likely to require firms to explain how the software makes decisions, but that often isn&#8217;t easy to unwind. The third is figuring out how to manage algorithms that learn and adapt; while they may be more accurate, they also can evolve in a dangerous or discriminatory way.</p>
<p>Though AI offers businesses great value, it also increases their strategic risk. Companies need to take an active role in writing the rulebook for algorithms.</p>

AI Regulation Is Coming

For years public concern about technological risk has focused on the misuse of personal data. But as firms embed more and more artificial intelligence in products and processes, attention is shifting to the potential for bad or biased decisions by algorithms—particularly the complex, evolving kind that diagnose cancers, drive cars, or approve loans. Inevitably, many governments will feel regulation is essential to protect consumers from that risk. This article explains the moves regulators are most likely to make and the three main challenges businesses need to consider as they adopt and integrate AI. The first is ensuring fairness. That requires evaluating the impact of AI outcomes on people’s lives, whether decisions are mechanical or subjective, and how equitably the AI operates across varying markets. The second is transparency. Regulators are very likely to require firms to explain how the software makes decisions, but that often isn’t easy to unwind. The third is figuring out how to manage algorithms that learn and adapt; while they may be more accurate, they also can evolve in a dangerous or discriminatory way. Though AI offers businesses great value, it also increases their strategic risk. Companies need to take an active role in writing the rulebook for algorithms.

AI Regulation Is Coming

Summary.

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