Sinan Aral

🚨Out now in PNAS! The first ever (we believe) large scale RCT + field experiment on the performance effects of AI Personalization!

🚩 In a preregistered randomized experiment,
🚩 We paired 1,258 participants with AI agents prompted to exhibit varying levels of the Big Five personality traits.
🚩 These human–AI teams produced 7,266 display ads, evaluated by 1,168 human raters, and a field experiment on X with ~5M impressions.

🚨Let's not forget that the cost of achieving a fixed level of AI performance has dropped by roughly 47% every quarter since 2023 (about a 13-fold decrease each year).

Another great conversation on @SquawkCNBC, this time with @BeckyQuick about the impending @AnthropicAI IPO! We talked about the valuation, revenue multiples, competitive pressure on margins and, most importantly, where competitive advantage comes from when raw intelligence becomes commoditized.

So much to learn and talk about! Thanks for having me.

🚩 New Paper! The results of our MIT International AI Negotiations Competition are now out now in @PNASNews.

We facilitated ~200,000 AI Agent Negotiations across multiple diverse scenarios and objectives in which participants iteratively designed and refined AI negotiation agents. Our findings revealed that

🚩 Fundamental principles from established human-human negotiation theory remain crucial in AI-AI negotiations. Specifically,

🚩 AI agents exhibiting high warmth fostered higher counterpart subjective value and reached deals more frequently, which enabled them to create and claim more value in integrative settings (who says AI agents are only rational optimizers?).

However,

🚩 Conditional on reaching a deal, warm agents claimed less value while dominant agents claimed more value. These results align with classic negotiation theory emphasizing relationship-building, assertiveness, and preparation.

🚩 Our analysis also revealed unique dynamics in AI-AI negotiations not fully explained by negotiation theory, particularly regarding the effectiveness of AI-specific strategies like chain-of-thought reasoning and prompt injection.

🚩 The agent that won our competition implemented an approach that blended traditional negotiation preparation frameworks with AI-specific methods.

Together, these results suggest the importance of establishing a new theory of AI negotiations that integrates established negotiation theory with AI-specific strategies to optimize agent performance. Our research suggests this new theory must account for the unique characteristics of autonomous agents and establish the conditions under which traditional negotiation theory applies in automated settings.

🚩 Critically, we are releasing all the prompts and all the transcripts of all the negotiations publicly to support replication and future research.

Kudos to first author @MichelleVaccaro and the rest of the team including Jared Curhan @caosunova @harangju. Major thanks to cosponsors the @mit_ide and @iDecisionGames! We also thank @OpenAI for model access, and @MITSloanExecEd and the MIT Office of Teaching and Learning for institutional support. We are grateful to all participants in the MIT AI Negotiations Competition for their engagement and creativity. Their innovative approaches significantly contributed to our understanding of AI negotiation dynamics.

pnas.org/doi/10.1073/pn…

As always, thoughts and comments highly encouraged!

🚩 New Work on The Clarity Act

Everyone is talking about the #ClarityAct, which aims to allow some crypto tokens to be regulated as commodities, not securities... It could change the #Crypto industry dramatically.

🚩 But the "Mature Blockchain Test" embedded in the Act establishes a 'decentralization requirement' for crypto networks, which states that no single entity or affiliated group can unilaterally modify the protocol, control governance, or hold more than 20% of the token supply or outstanding voting power.

🚩 Once a network certifies that it meets these decentralization benchmarks, the asset is treated as a digital commodity rather than an investment contract. This exempts the asset from strict SEC registration rules.

🚩 That's a huge shift. But there's also a huge problem:

🚩 We have not had good measures of crypto decentralization and decentralization is notoriously hard to measure.

🚩 That's why we built the MIT Framework for Logitudinal Analysis of Crypto Decentralization, which establishes clear, routinized and rigorous measures of Crypto Decentralization.

🚩 We also measured decentralization across 7 prominent blockchains over the life of their existence and

🚩 Developed a real time dashboard of Crypto Decentralization. You can find the MIT Crypto Decentralization Dashboard here:
lnkd.in/egF8Ge-V

These measures should be adopted as part of the standard for determining when a token can move from a registered SEC investment to a commodity.

You can read the paper here:
dl.acm.org/doi/epdf/10.11…

As always, we'd love to hear your thoughts and reactions!

Cc @harangju @EhsanValavi Madhav Kumar and @mit_ide

#clarityact #Crypto #Cryptocurrency #bitcoin #coinbase