sábado, 11 de abril de 2026

The Paradox of Humility: Europe's Proudest Values May Be Its Deepest Startup Failure



Building on my previous post (linked above), it is worth disclosing the results of a French study published in the Strategic Entrepreneurship Journal showing that expressed humility plays a decisive role in early-stage investors' funding decisions. The study shows that humility increases perceived likeability, trustworthiness, and the belief that founders can build strong teams. In pitch contexts, it functions as a relational signal under uncertainty. However, humility is not unambiguously rewarded. It is a double-edged signal: while it strengthens perceptions of relational capacity, it can also raise doubts about decisiveness and agency, as investors rely on simplified heuristics when evaluating entrepreneurs. https://sms.onlinelibrary.wiley.com/doi/10.1002/sej.70016

There is, however, a fact the study does not advertise: France is not Silicon Valley. It is a market where startup exits are rarer, unicorns thinner on the ground, and venture capital a fraction of what flows through the American ecosystem. Which raises an uncomfortable question: what if the investor behaviour this study measures is itself part of the problem? If French investors reward humility and American investors reward audacity — and American startups consistently and dramatically outperform European ones — then Europe may not simply be playing the game differently. It may be losing it, partly by design, rewarding precisely the founder signals least associated with breakout success.

This connects to a broader mechanism: entrepreneurial evaluation operates through competing prototypes of what a "successful founder" looks like, and those prototypes are not culturally neutral. Against the backdrop of my earlier post on immigrant and minority entrepreneurship — where evidence from The Economist and MIT studies shows that immigrants and ethnic minorities disproportionately drive startup creation — the pattern sharpens further. People shaped by adversity, displacement, and systemic exclusion appear to develop precisely the adaptive capacity that conventional evaluation systems struggle to recognise, and often penalise. The startup paradox, then, is not merely that the traits most useful under uncertainty are undervalued. It is that the evaluation systems themselves may be selecting for comfort over capability, for legibility over potential.

P.S. — If the signals that feel socially virtuous within European pitch rooms are systematically disadvantaging European founders in global competition, then the question I raised in October 2024 — should Europe emulate America's cutthroat, psychopathic "culture"? — is no longer rhetorical. Europe has spent decades congratulating itself on its social sophistication. The startup gap suggests that sophistication may have a price, and that entrepreneurs, not investors, are the ones paying it. https://19-pacheco-torgal-19.blogspot.com/2024/10/align-act-accelerate-can-europes-risk.html

Update after 4 days - Blogger analytics indicate that the majority of views for this post come from the USA (24%), Germany (9%), the UK (5%), and France (5%). 

quarta-feira, 8 de abril de 2026

Two Love Letters to a Science Struggling to Remember What Really Matters and the Unexpected Gift of the 2026 Hormuz Crisis


The first letter responds to Park and Suh’s article in Technological Forecasting and Social Change, which overlooks the role of serendipity in scientific discovery. It relies heavily on patent counts as indicators of technological contribution, ignoring their limitations. Of the roughly 50 million patents granted worldwide, most are, as The Economist puts it, an “intellectual junkyard” — ideas that never materialized, failed concepts, or filings with no real intent to succeed. Even high-profile failures illustrate this flaw: Theranos, one of Silicon Valley’s most notorious frauds, held over 100 patents and reached a $10 billion valuation. Empirical evidence reinforces the point: a large-scale study of 4,460 real-world innovations found that most were never patented, with patents capturing only about 15% of actual innovation.  https://zenodo.org/records/18951538

The second letter responds to Haunschild and Bornmann’s article in the Journal of Informetrics, which proposes a bibliometric method to identify “bright young scientists” based largely on publication counts in high-impact journals. This approach is not only flawed but likely to exacerbate existing distortions in science. Journal impact factors are aggregate metrics that cannot capture the quality, originality, or intellectual risk of individual work; using them as proxies for talent is a textbook ecological fallacy. More importantly, institutionalizing such criteria would intensify perverse incentives already at play. This proposal would accelerate hyperauthorship, strategic publishing, and superficial output. Far from identifying genuine talent, the proposed method risks systematically amplifying the very behaviors that undermine it. https://zenodo.org/records/19001905 

PS - The 2026 Strait of Hormuz energy crisis did what years of sustainability advocacy could not: it made Europe's dependence on fossil-based construction materials impossible to ignore. The paradox is almost elegant: it took a fossil fuel crisis to make the case for leaving fossil fuels behind, and in its wake, bio-based construction materials finally emerged from niche experiments to serious contenders, offering a tangible path toward a more resilient and low-carbon built environmenthttps://www.preprints.org/manuscript/202604.0356

terça-feira, 7 de abril de 2026

AI and the Forecasting of Scientific Futures

 

https://19-pacheco-torgal-19.blogspot.com/2026/04/can-ai-discover-what-humans-cannot.html

Building on a previous post (linked above) I disclose yet another interesting paper by researchers from the University of Illinois Urbana-Champaign. If the previous post asked whether AI can discover what humans cannot, this paper asks something equally audacious: can AI predict where science is going before it gets there?

The authors make a deceptively simple but radical move: they reframe research proposal generation as a forecasting problem. Given a question and a body of literature available before a fixed cutoff date, the model generates a structured proposal — evaluated not by how sophisticated it sounds, but by how accurately it anticipates research directions that actually materialise in papers published afterwards. Trained on 17,771 papers, the system learns to spot overlooked gaps and draw inspiration across disciplinary boundaries — precisely where the most consequential ideas tend to hide. The implications reach well beyond academia. This could become the instrument through which funding agencies, science policymakers and research evaluators make higher-stakes decisions: not which proposals sound compelling in committee, but which ones the arc of science is already bending towards.  https://arxiv.org/abs/2603.27146

Yet the promise comes with a shadow. If funding decisions and research agendas start leaning on AI forecasts, there is a risk of reinforcing existing patterns rather than fostering genuine innovation. By privileging areas the model predicts will succeed, we could inadvertently narrow the scope of exploration, crowding out high-risk, unconventional ideas that fall outside the AI’s learned trajectories. Over time, this might entrench a “predictable science,” where AI-guided choices favor incremental advances and safe bets, undermining the serendipitous leaps that often drive paradigm shifts.

P.S. — The above-mentioned paper cites a compelling companion work: PreScience: A Benchmark for Forecasting Scientific Contributions, which approaches the same ambition from a different angle — benchmarking how well AI can anticipate the actual future impact of not-yet-published research. Taken together, these two papers signal something significant: a new subfield is quietly assembling itself, one that treats scientific forecasting not as speculation, but as a rigorous and measurable discipline.  https://arxiv.org/abs/2602.20459