Digital Platforms

Bringing Behavioral Economics Theory to Practice: My research focuses on the economic drivers of digital trust erosion, particularly the externalities caused by misinformation in two-sided marketplaces (e.g., social networks, e-commerce platforms). Using Nobel Prize-winning economic theories from Spence, Coase, and Stiglitz, van Alstyne, 2023 proposes that consumer harms from misinformation be measured through the magnitude of decision errors induced by misleading claims. This quantifiable metric allows us to internalize market externalities and design interventions that achieve equilibrium between content producers and consumers.

Building a Real-time Online Advertising Marketplace

To test these theories, in the past year, I helped my PIs set up the Platform Governance lab at BU and MIT, and developed an experimental marketplace where advertisers escrow a “truth warrant” — a monetary deposit signaling the credibility of their claims (aka providing advertisers the option to ‘put their money where their mouth is’). In our ads market, consumers can challenge misleading claims at a nominal cost, with disputes adjudicated by a peer jury. In over 1,350 rounds of human-buyer experiments, this intervention:

1. Increased profits for honest advertisers.
2. Penalized deceptive advertisers, significantly reducing their profitability.

Creating Reproducible Behavioral Experiments with Human Participants

In our research, we have created reproducible infrastructure to run interactive online experiments at scale. The marketplace supports experiments where we can run tens of parallel “games” with 5-8 advertisers and 5-8 buyers in an e-commerce setting that captures the intricacies of online sales for both sides e.g. choosing how accurately product quality is reflected in an advertisement, selecting from a number of products to purchase, having a limited wallet to spend money, relying on reviews and adding ratings after learning of a product’s true quality, post-purchase. Modeling online sales is a challenging process, and we make it seamless, in order to reflect these complexities. In our framework, built atop MIT’s Empirica library, we can now launch online sales experiments at the click of a button.

Impact on Platform Design

By redesigning platform incentives, my research provides actionable insights for policymakers and platform operators. Key findings include:

1. Introducing economic costs for misinformation production reduces its prevalence.
2. Transparent mechanisms like escrow-based truth warrants enhance accountability while preserving free speech.
3. Platforms benefit economically from reduced misinformation as user trust and engagement improve.

I demonstrated how platforms could integrate mechanisms like truth warrants to reduce misinformation without resorting to censorship or central authority. Field experiments are underway to compare human and bot participants’ strategies in two-sided marketplaces under different incentive structures. We are also designing a political marketplace to test these theories on social networks.

Intervening on Manipulative “GenAI” Sellers

Generative artificial intelligence and ‘agentic’ sellers are already supporting advertisers in online marketplaces like Amazon and eBay. It is extremely important to develop economic models of their benefits as well as a risk assessment of the potential harms, in light of the risks from deploying GenAI in consumer-facing applications.

Our marketplace was extended to analyze agentic sellers using large language models (LLMs) can affect sales. Results showed that while GenAI/LLM sellers employed deceptive strategies to maximize sales in control settings (‘Reputation Market’), the truth-warrant mechanism (‘Warrants’ market) curtailed these behaviors effectively.