Pith. sign in

REVIEW 1 cited by

Artificial Influence: An Analysis Of AI-Driven Persuasion

Not yet reviewed by Pith; the record is open.

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2303.08721 v1 pith:CEZGSNBA submitted 2023-03-15 cs.CY cs.AIcs.CLcs.LG

classification cs.CYcs.AIcs.CLcs.LG
keywords persuasionsystemspersuasiveai-drivenfuturealterartificialexamine
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Persuasion is a key aspect of what it means to be human, and is central to business, politics, and other endeavors. Advancements in artificial intelligence (AI) have produced AI systems that are capable of persuading humans to buy products, watch videos, click on search results, and more. Even systems that are not explicitly designed to persuade may do so in practice. In the future, increasingly anthropomorphic AI systems may form ongoing relationships with users, increasing their persuasive power. This paper investigates the uncertain future of persuasive AI systems. We examine ways that AI could qualitatively alter our relationship to and views regarding persuasion by shifting the balance of persuasive power, allowing personalized persuasion to be deployed at scale, powering misinformation campaigns, and changing the way humans can shape their own discourse. We consider ways AI-driven persuasion could differ from human-driven persuasion. We warn that ubiquitous highlypersuasive AI systems could alter our information environment so significantly so as to contribute to a loss of human control of our own future. In response, we examine several potential responses to AI-driven persuasion: prohibition, identification of AI agents, truthful AI, and legal remedies. We conclude that none of these solutions will be airtight, and that individuals and governments will need to take active steps to guard against the most pernicious effects of persuasive AI.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Verbalized Bayesian Persuasion

    cs.GT 2025-02 conditional novelty 7.0 of 10

    VBP solves Bayesian persuasion in natural language by treating LLMs as sender and receiver in a mediator-augmented game and searching prompt strategies with Prompt-PSRO.

Pith tools