+ THREE INSIGHTS FOR THE WEEK |
1. Technological innovation works best when it’s grounded in collective wisdom. So argues Alex “Sandy” Pentland in his new book, “Shared Wisdom: Cultural Evolution in the Age of AI,” which calls on business and policy leaders to build a digital society that protects individual and community autonomy.
In making his case, Pentland, a Stanford HAI fellow and the Toshiba Professor at MIT, examines the effects of earlier artificial intelligence systems on society, among them:
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AI in 1960: Logic and optimal resource allocation emerge.
- AI in 1980: Expert systems automate tasks where specialists are expensive or scarce.
- AI in the 2000s: User data enables “collaborative filtering” that targets individuals based on their behavior.
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Understanding both the impact and unintended consequences of those earlier systems can help us in developing technologies that aid, rather than replace, our human capacity for deliberation, Pentland writes.
“With some changes to our current systems, it is possible to have the advantages of a digital society without enabling loud voices, companies, or state actors to overly influence individual and community behavior,” he writes.
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2. Leaders who push to have employees in the office four or five days a week are fixated on the wrong problem, according to productivity experts Brian Elliott, Nicholas Bloom, and Prithwiraj Choudhury.
Writing in MIT Sloan Management Review, the authors argue that hybrid work is not a policy challenge but a leadership capability challenge.
Rather than cranking up in-office days per week, business leaders should concentrate on building organizational strength that drives superior business results, regardless of a worker’s location.
The researchers recommend developing four capabilities that drive hybrid work success:
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Know your talent edge. With your organization’s competitive advantage in mind, determine how flexibility might support broader business objectives and help you compete for top talent.
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Measure results, not presence. Shift from monitoring activity to measuring outcomes. Transparent goal setting and progress tracking builds alignment and trust while addressing proximity bias, which works against employees who have caregiving responsibilities.
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Let teams lead the way. Empower teams to create their own working agreements that match their specific collaboration needs, whether that means establishing guaranteed overlap time or choosing certain days for in-person work.
- Invest in getting better. Redesign office spaces for part-time use with more collaboration areas; budget for intentional team gatherings; and provide management training on leading distributed teams.
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3. Will AI lead to better financial decisions? A new research group from the MIT Initiative on the Digital Economy is considering that question. The group, AI in Financial Markets and Decision-Making, is led by MIT Sloan professor Eric So.
In a recent Q&A, So shared his take on which developments business leaders should keep an eye on as AI continues to impact finance:
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Whether AI can improve company valuations. So’s team will study whether large language models can aggregate information more effectively than human experts can, by measuring AI “reasoning traces” to understand the computational effort required to properly value a firm.
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The risk of homogenized decision-making in financial markets. Does the “wisdom of the crowd” disappear when information sources become uniform? So plans to test whether relying on identical AI-generated summaries erodes the diversity of perspectives that leads to better market outcomes.
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How technology changes trading behavior. Beyond AI, So’s research explores what happens when investors shift to smartphone-based trading platforms — and how these technological shifts affect investor welfare and performance.
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Dynamic work design, explained
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Stalled projects and workarounds cause chaos in too many organizations. There’s a better way forward.
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Traditional management frameworks and workflows assume that the world is static.
That assumption is costing organizations. Annual budgets get locked in months before the fiscal year begins and then become obsolete at the first market shift. Workers facing unexpected changes create workarounds to get things done — workarounds that proliferate and lead to organizational chaos.
MIT Sloan professor Nelson Repenning and senior lecturer Donald Kieffer have an alternative: dynamic work design. It's about uncovering problems in a way that makes them solvable, often by starting small rather than seeking wholesale transformation.
As explained in their new book, “There’s Got To Be a Better Way: How To Deliver Results and Get Rid of the Stuff that Gets in the Way of Real Work,” dynamic work design rests on five principles:
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Solve the right problem — and solve the problem right.
- Structure for discovery.
- Connect the human chain.
- Regulate for flow.
- Visualize the work.
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Our new explainer delves into each principle, paired with real-world examples of how dynamic work design can save organizations money and get them moving again when they’re stuck.
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– Lawrence Schmidt, Associate Professor of Finance, MIT Sloan
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