Society and organizations invest heavily in selecting the best leaders, and existing research shows a positivity bias by focusing on the bright side of leadership. Should we focus on finding the best leaders or avoiding the worst? Our new paper provides robust evidence for an “avoid-the-worst” principle in human leadership preferences. We found that the top 100 business schools emphasize good leadership far more than the prevention of bad leadership. But actual employee experiences from 9.9 million Glassdoor reviews show that people mentioned their leader 70% more often in the negative than positive section, and negative leader mentions predicted company ratings 1.5 times more strongly. A bad-leader mention was also associated with 30% higher odds of leaving a company within the first year among former employees, whereas a good-leader mention is associated with only 5% lower odds of leaving. We also have causal evidence across 40 countries (N = 51,433) revealing that people were more willing to sacrifice time and money to avoid a bad leader than obtain a good leader (across both morality and competence). Our research suggests that people care more about avoiding the worst leaders than getting the best. But our leading schools are focused on the opposite issue. The central question of institutional design may not be who should rule, but how to prevent bad leaders from doing too much damage. This research was led by @H_Sjastad and @jareefbnmartuza Read the full paper here: osf.io/preprints/psyarxiv/8g…

The Unreasonable Effectiveness of AI in Mathematics politicalcalculations.blogsp… "AI is pressing them [mathematicians] to become more productive than they've ever been before. How will they adapt? And for that matter, how many other professions will soon find themselves in a similar situation?"

There is widespread frustration about the AI industry’s “automate everything" agenda. But what would it take to steer AI toward augmenting human capabilities instead? In a new essay, Gabriel Unger (@_gabrielunger) and I lay out a research agenda and plan for action. normaltech.ai/p/steering-ai-… Our thesis is that the reason why AI-for-automation currently dominates isn’t just economic incentives but also deeper cultural issues in computer science as a field. And that can be changed. - We sketch four important research directions that are needed in order to build collaborative or augmentative AI. The automation paradigm largely ignores these technical challenges. - We advocate for Human-Computer Interaction and Human-Centered AI to be elevated as a subfield in status, influence, and funding, and changing AI curricula to emphasize the role of the human and decrease the centrality of the pure-automation problem framing. - We point out that there are a surprising number of efforts in economics, computer science, industry, and policy all trying to bring about a shift toward augmentation, but not enough collective awareness. Better connecting these movements would amplify their power. - We think the automation agenda is struggling on its own terms. Compiling evidence of the limits of general-purpose agents for automation and loudly making the case will encourage more companies to take collaboration more seriously as a goal. - We predict that once more workers experience this way of working and recognize that there are alternatives to the delegate-and-supervise pattern, it will generate more demand, creating a flywheel effect. - Targeted policy levers can play a small but important role in amplifying both the supply and demand for pro-worker AI. We don’t need clumsy top-down mandates. We're not against automation. But we think the goal of AI must be broader. This is the start of a long-term project. I know there are far more like-minded efforts out there than we’re aware of. I’d love to hear about some of them.

Get ready for the great philosophy of AI hiring spree of 2027. All posted in just the last 48 hours. Do we even have enough philosophers of AI to meet demand?

"Checking the Classifieds" is an investigation into foreign espionage on American campuses. Using advanced Advertising Intelligence (ADINT), we uncover evidence that the CCP may still be siphoning hypersonic missile tech from Alfred University. nas.org/reports/checking-the…

"Holding students’ academic performance and interests constant, teachers are less likely to recommend demanding academic tracks when students come from disadvantaged socioeconomic backgrounds...teachers overestimate the probability high-achieving disadvantaged students will fail"

My district referendum is just shy of $300,000,000 and slated for repair, replacement, and maintenance of HVAC, roofing, etc. This stuff should’ve been factored into the budget for the last several years. They need to live within the currently already high tax dollars they get from us, just like residents have to live within their means.

I’m often asked by university advocacy groups - which champion academic principles - how they can help reform universities. They sometimes add that they have a line into senior administration and believe they can effect change. In practice, universities typically offer these groups polite assurances and symbolic engagement, while continuing to operate as before. The core problem is transparency. Universities speak fluently about academic freedom, due process, open inquiry, free speech, and shared governance. These principles are carefully codified in policies, handbooks, and public statements for faculty and students alike. Yet in reality, opaque administrative structures function very differently - making unilateral decisions behind closed doors, operating in secrecy, and relying on nondisclosure agreements to conceal actions they do not want to be subject to public scrutiny. As a result of these tactics, the true scope of administrative control inside universities remains largely invisible to the public.