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AI

The AI Payoff Is Real. The Timeline Is the Problem.

Yale SOM’s Jeffrey Sonnenfeld, computer scientist and entrepreneur David Siegel, and co-author Stephen Henriques argue that investors are counting on short-term returns from a technological transformation that will take years to deliver on its promise.

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  • To Shift Opinions in Online Conversations, Start by Building Trust

    New research from Yale SOM’s Tauhid Zaman suggests that starting by establishing common ground makes it possible to make connections and even change some minds.

    An illustration of twitter-style birds arguing
  • Now It’s Personal: How Knowing an Ad Is Targeted Changes Its Impact

    A consumer’s knowledge that an advertisement has been tailored to their interests changes how they respond, according to a new study co-authored by Yale SOM’s Jiwoong Shin. Firms evaluating marketing strategies should factor consumers’ inferences about targeted ads into their advertising decisions, Shin says.

    An illustration of a bald man looking at an ad for a hair growth product that includes a version of himself with hair
  • Can We Protect Our Election from the Bots?

    More than 50,000 Russia-linked bots were active on Twitter during the 2016 election. Are they back? We talked with Prof. Tauhid Zaman, who has carried out a series of studies identifying bot networks and assessing their impact.

    A photo illustration of legions of toy robots
  • Machine Learning Model Extracts Insights from Customer Reviews

    A new study co-authored by Yale SOM’s K. Sudhir uses natural-language analysis to learn from what customers are saying—and to infer meaning from what remains unsaid.

    An illustration of artificial intelligence
  • Online and Off, We Are Drawn Toward Those with Similar Writing Styles

    Both online and in-person friendships are more likely to develop between people who have similar linguistic styles, according to a new study co-authored by Balázs Kovács at Yale SOM.

    An illustration of overlapping profiles
  • Can Big Data Fight a Pandemic?

    The COVID-19 crisis has intensified the debate over big data and privacy. Governments are pulling together data from public and private systems in order to predict and counter the spread of COVID-19. But setting aside privacy protections in a time of crisis could lead to new, permanent norms.

    An illustration of an eye made out of data with an image of the COVID-19 virus in the center
  • Are Electronic Health Records Useful Yet? 

    The story of EHRs serves as a prelude to what we’re experiencing today in almost every facet of our lives: a utopian promise of ubiquitous data tempered by technical challenges and concerns over privacy.

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  • How Machine Learning Can Find Extremists on Social Media

    Yale SOM's Tauhid Zaman investigated how artificial intelligence could assist efforts to detect and suspend extremist accounts, before they are used to recruit members and spread propaganda.

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  • Researchers Propose New Method to Hedge against the Risk of Climate Disaster

    Markets could be a huge part of mitigating climate risk. A proposal from Yale finance faculty seeks to make that a reality.

    Firefighters battling the Getty fire in the Brentwood Heights neighborhood of Los Angeles on October 28, 2019. Photo: Brian van der Brug/Los Angeles Times via Getty Images.
  • Will Machine Learning Transform Finance?

    Charles Elkan, Goldman Sachs’ global head of machine learning, on the technology can extract value from the natural resource that is defining this century—data.

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