Data: Global Business, AI’s Inabilities, and the Joy of Spending

THOUGHT

“Let’s be honest: Saving is no fun. People don’t get ‘utils’ [utility] out of saving. They get utils out of spending.”

Wharton business economics and public policy professor and Pension Research Council executive director Olivia S. Mitchell addressed this topic at the Council’s 2024 symposium, which explored how noncognitive skills — soft personality traits like conscientiousness, stress resistance, grit, and locus of control — impact retirement readiness.

DATA INTERPRETED

Startups raised this much more in their first year when using an accelerator.

A paper from Wharton management professors Valentina Assenova and Raffi Amit shows that participating in accelerators generally leads to positive outcomes in terms of startup business success rates. In examining data from 8,580 fledgling companies that made it past the initial screening stage at 408 accelerators in 176 countries between 2013 and 2019, the professors found that accelerated startups generated more revenue, on average, than their peers.

THOUGHT

Why AI Can’t Replace You at Work

Workers can stop worrying about being replaced by generative artificial intelligence.

Wharton experts Valery Yakubovich, Peter Cappelli, and Prasanna Tambe believe it isn’t going to happen as drastically as many predict. In an essay published in the Wall Street Journal, the professors contend that AI will most likely create more jobs for people, because it needs intensive human oversight to produce usable results. “The big claims about AI assume that if something is possible in theory, then it will happen in practice. That is a big leap,” they wrote. “Modern work is complex, and most jobs involve much more than the kind of things AI is good at — mainly summarizing text and generating output based on prompts.”

Yakubovich spoke to Wharton Business Daily, offering several key facts he hopes will allay people’s fears of robotic replacement. First, while generative AI has advanced rapidly, it still has a long way to go before it can function autonomously and predictably, which are key features that would make it reliable. Second, large language models (LLMs) like ChatGPT are capable of processing vast amounts of data, but they can’t parse it accurately and are prone to generating misleading information, known as AI hallucinations. “You get this output summary — how accurate is it? Who is going to adjudicate among alternative outputs on the same topic? Remember, it’s a black box,” said Yakubovich, who is executive director of the Mack Institute for Innovation Management.

Third, companies are risk-averse and need to maintain a high degree of efficiency and control to be successful, so they won’t be rushing to lay off all their people in exchange for technology that still has a lot of bugs to work out. “If we are thinking 40, 50 years ahead, that’s wide open,” Yakubovich said. “The issue we are discussing now is the very specific [needs] for business. The risk for companies is very high, and they are not going to move very fast.”

Data science has been around for years, Yakubovich said, yet many companies still lack good infrastructure to organize the tremendous quantity of information that the technology can collect. Even if they built it, humans are still an indispensable part of making sense of it all. “If you want to curate everything, it’s a lot of work,” he said, “and this is where more jobs will emerge.” —Angie Basiouny

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Daily average of repo transactions

Broker-dealers have monopsony power in repo (repurchase agreement) financing that inflates their profits and could impact the broader economy, according to a study by Wharton finance professor Amy Wang Huber. She used a structural model to estimate the difference between what dealers pay to the lenders for getting cash and what dealers charge their customers for using that cash, showing that dealers’ market power over cash lenders affects many downstream asset prices.

THOUGHT

“We’re concerned about who owns what company, whether it be TikTok or whether it be semiconductors. National identity really matters, and that’s got to be part of the equation.”

Witold Henisz, vice dean and faculty director of the ESG Initiative, on how business leaders are facing a new set of questions to mitigate risk in global companies’ operations. Henisz discussed his new book, Geostrategy by Design, on the Ripple Effect podcast. The episode was part of the “Meet the Authors” series.

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Reduction of emissions needed by 2030 to meet the United Nations standard for limiting global warming

Electrifying everything is an attractive pathway to meeting the U.N. goal of achieving net-zero emissions by 2050, based on a Penn “Energy Week” panel moderated by Wharton legal studies and business ethics professor Sarah Light. The climate and energy provisions in the 2022 U.S. Inflation Reduction Act will call for an outlay of $1,045 billion over 10 years, according to estimates by the Penn Wharton Budget Model.

Published as “Data” in the Fall/Winter 2024 issue of Wharton Magazine.