Does AI Help Reduce Wasteful Holiday Gifting?

Reading Time:


MIT SMR Strategy Forum

The MIT SMR Strategy Forum offers monthly insights from academic experts on pressing strategy issues related to business, management, technology, and public policy.
More in this series

To close out 2022, we asked the MIT SMR Strategy Forum panel to weigh in on a lighter topic than usual: holiday gift giving. Finding the perfect gift for a loved one can be a challenging, and even stress-inducing, task. No one wants to give (or receive) a gift that will go unused, leaving many to argue that cash or gift cards, while impersonal, remain king. And holiday gift giving has long been a topic of interest for economists, including Strategy Forum panelist and economist Joel Waldfogel. His 1993 paper “The Deadweight Loss of Christmas,” published in The American Economic Review, famously posited that holiday gift giving destroys a significant portion of the retail value of gifts and results in the problem of “deadweight loss,” given that the best that gift givers can do is to replicate the choice their gift receivers would have made themselves.

With AI-driven product recommendations now a mainstay of e-commerce, we asked our panel of experts to respond to the following statement: Artificial intelligence is reducing wasteful holiday giving (i.e., deadweight loss) by helping online retailers to better match people to presents.


Just under half of the responding panelists (48%) either disagreed (38%) or strongly disagreed (10%) that AI is helping to reduce wasteful holiday giving.

Tom Lyon of the University of Michigan and Monika Schnitzer of Ludwig Maximilian University both point out that while AI engines are becoming more sophisticated at recognizing what we as individuals might want to purchase for ourselves (based on myriad data), they still lag in helping us buy for others. Likewise, economist Preston McAfee writes, “I think AI could help with the matching of people and presents, but I’m not seeing it in action at this time, nor is the kind of data needed — recipient characteristics — available to use.”

Strongly disagree

If a retailer is employing AI to recommend products to consumers and the AI has been trained on what people usually shop for around Christmas, then in all likelihood it is exacerbating rather than mitigating waste.
Timothy Simcoe
Joshua Gans
Rotman School of Management

The Wharton School’s Lori Rosenkopf challenges the idea that AI recommendations can address the issue of deadweight loss, noting that in fact “if recommendation engines pull gift givers away from cash or fungible gift cards, deadweight loss is likely to increase.”

Another common refrain among those in the “agree” category: Gift giving is about thoughtfulness, not just precise matching. Petra Moser of the NYU Stern School of Business says that AI recommendations miss “the point of gift giving: thinking about the other person and what would make them happy.”


I suspect that many would not adopt these systems because they feel inconsistent with the norms of gift giving.
Timothy Simcoe
Olav Sorenson
UCLA Anderson School of Management

Neither Agree nor Disagree

Nineteen percent of respondents fall somewhere in the middle, noting that although there are ways in which AI can facilitate better gift giving, there’s still room for waste and error.

Joel Waldfogel of the University of Minnesota (and original “Deadweight Loss of Christmas” author) writes that it’s “not clear that AI, per se, is magic here.” For him and several others on the panel, a key issue is that in order to be more useful, AI recommendation engines need more data about the recipient — from retail browsing behavior to personal interests. As Waldfogel points out, gaining access to such data “requires either opting in by the recipient or seeming breaches of privacy.”

Anita McGahan of the University of Toronto notes that AI-driven gift giving has its pros (namely, facilitating competitive pricing and reducing delivery costs) and cons (it can remain wasteful and induce unnecessary purchases) but points out that there is “real opportunity in AI-facilitated cultural change to reduce unnecessary consumption altogether.”

Harvard Business School’s Shane Greenstein points out that despite AI’s advantages in helping people find gifts, there’s no accounting for taste.

Neither agree nor disagree

AI does not enhance the taste of a distant relative who intends to buy a tacky sweater. It makes the tacky sweater easier to find.
Timothy Simcoe
Shane Greenstein
Harvard Business School


A third of the panelists either agree (28.5%) or strongly agree (5%) that AI is reducing wasteful giving. Erik Brynjolfsson of Stanford notes that recommendation and matching is where AI has excelled for some time: “Recommender systems are one of the oldest and most successful uses of AI. They are far from perfect, but they’re often better than human store clerks at finding appropriate presents for me to give.”

Nicolai Foss of Copenhagen Business School says that improvements in AI technology continue to reshape retail markets, and with that, it “may be expected to reduce waste by improving the matching of people and presents.”

Timothy Simcoe of Boston University agrees that AI is improving gift giving, at least at the margins, but notes that an analog technology may still reign supreme: the Christmas wish list. “That already works pretty well — except for a few unnamed relatives, who are giving me socks no matter what Amazon tells them,” he adds. And Ashish Arora of Duke University points to another tried-and-true technology for matching people to what they want at the holidays that long predates AI: cash!


MIT SMR Strategy Forum

The MIT SMR Strategy Forum offers monthly insights from academic experts on pressing strategy issues related to business, management, technology, and public policy.
More in this series

More Like This

Add a comment

You must to post a comment.

First time here? Sign up for a free account: Comment on articles and get access to many more articles.