Technology

Digital technology, AI, and their social effects.

Video Games and Wellbeing: Separating Moral Panic from Evidence

nonacademicresearch.org Editorial · May 10, 2026 · submitted by nonacademicresearch.org Editorial · nar:6qakbf1gm8ocqqqthc

Despite decades of concern about video games' effects on aggression, mental health, and academic performance, the evidence shows effects are small, context-dependent, and frequently overstated in public discourse. Some gaming — particularly action gaming in moderate amounts — may improve certain cognitive abilities. Problem gaming (gaming disorder) affects a small minority of players. The blanket framing of video games as harmful is not supported by the best available evidence.

Online Misinformation: What the Evidence Shows About Spread and Effects

nonacademicresearch.org Editorial · May 9, 2026 · submitted by nonacademicresearch.org Editorial · nar:696w5ct9ayucxylb6n

Concern about the spread of false information online has prompted extensive empirical research over the past decade. A major MIT study found that false news spread faster and wider on Twitter than true news, driven by novelty and emotional content rather than bots. However, subsequent research has found that consumption of political misinformation is concentrated among a small fraction of users, and that the relationship between misinformation exposure and belief or behavior change is weaker than often assumed. Correcting misconceptions is possible but requires sustained, credible sources.

Algorithmic Bias: Evidence for Discrimination in Automated Systems

nonacademicresearch.org Editorial · May 9, 2026 · submitted by nonacademicresearch.org Editorial · nar:aya4d3uwucbuhxsaht

Automated decision-making systems — used in hiring, lending, criminal justice risk assessment, and healthcare — have been found to produce discriminatory outcomes across multiple studies and real-world audits. The evidence covers several distinct phenomena: facial recognition systems that are significantly less accurate for darker-skinned women than lighter-skinned men; recidivism prediction tools that are miscalibrated by race; and credit scoring models that encode historical patterns of discrimination. Whether these constitute bias in a morally actionable sense depends on contested frameworks for algorithmic fairness that are mathematically irreconcilable.

Automation and Employment: Does Technology Really Destroy Jobs?

nonacademicresearch.org Editorial · May 9, 2026 · submitted by nonacademicresearch.org Editorial · nar:9zpzd2omdqlokj7q2w

Fears that automation and technology permanently destroy employment have recurred since at least the Luddite movement of the early 19th century. The modern version — that robots and artificial intelligence will render large fractions of the workforce redundant — has generated extensive empirical research. The evidence is nuanced: automation does displace workers in specific tasks and occupations, and these transition costs are real and concentrated among particular workers and communities. But the historical pattern has been that technological change creates new kinds of work even as it eliminates old ones — though the distribution of gains has been highly unequal.

Social Media and Mental Health: What the Evidence Actually Shows

nonacademicresearch.org Editorial · May 9, 2026 · submitted by nonacademicresearch.org Editorial · nar:c1dkuupp6lq5fkqxy3

Public concern that social media use damages mental health — particularly among adolescents — has grown substantially since the mid-2010s. The empirical evidence is more mixed than public discourse suggests. While some longitudinal studies find associations between heavy social media use and depression or anxiety, effect sizes are typically small, causality is difficult to establish, and experimental studies have produced inconsistent results. Understanding what the evidence does and does not support is essential for sound policy.