Your Algorithm

Central banks are increasingly turning to artificial intelligence for tasks such as forecasting inflation, supervising banks and detecting financial risks. That raises a growing accountability question: if an algorithm contributes to a policy mistake or regulatory failure, it is unclear who bears responsibility. Commentators argue that central banks will need transparent governance, clear chains of responsibility and democratic oversight as AI becomes embedded in monetary and supervisory decisions.

The United States carried out a test in Nevada aimed at improving algorithms used to detect nuclear activity. The exercise, reported by Axios, is part of ongoing efforts to refine the country's nuclear monitoring capabilities, and it is drawing attention amid heightened global focus on nuclear proliferation and arms-control verification.

The first US trial against TikTok is set to test claims that the platform fueled a teen mental health crisis. The case will examine whether the app's design and algorithms contributed to harm among young users, and its outcome could shape the wave of similar lawsuits and regulatory pressure facing social media companies in the United States.

Regulators are drawing clear lines for medical AI, requiring that clinical tools be safe, fair, and accountable, with patient safety and clinical control placed above automation. The debate frames medical AI governance as a human rights test: developers and health providers must show algorithms do not discriminate, remain explainable, and keep doctors in charge of final treatment decisions.

Debate is growing over algorithmic pricing, with commentators asking who is accountable when automated systems determine what consumers pay. The discussion centres on whether current regulation is adequate to oversee AI-driven price setting in markets, and whether firms deploying such tools face sufficient limits to prevent collusion or unfair pricing practices against customers.

Zohran Mamdani is framing his politics around what he calls the 'greedy algorithm' of corporations, arguing that profit-driven corporate behavior is at the root of problems facing ordinary Americans. The approach signals a sharpened anti-corporate message as he builds a distinctive political brand, drawing attention from commentators and sparking debate over how far this new style of economic populism will reach beyond his base.

Quantum computing company EigenOrbit has released eigenkit, a new open-source software library for quantum computing. The announcement, reported by The Quantum Insider, makes the tools freely available to developers and researchers. The move positions EigenOrbit within the growing open-source quantum ecosystem, and could lower barriers for teams experimenting with quantum algorithms and workflows.

Companies are increasingly using artificial intelligence tools to help set employee pay, often without workers knowing. The Wall Street Journal reports that employers rely on algorithmic systems to benchmark salaries and determine compensation, raising questions about transparency, fairness and potential bias in how wages are decided across industries.

Al Jazeera asks whether Albania is becoming the European Union's testing ground for artificial intelligence in politics. The debate centres on the country's use of AI in government and what that means for democratic accountability in a state seeking EU membership. Observers are weighing whether the experiment offers a model for Europe or a warning about handing political roles to algorithms.

YouTube star MrBeast told billionaire Mark Cuban that he spends millions of dollars reverse engineering the algorithms on each platform so he never runs out of ideas. The revelation, made during a conversation with Cuban, highlights the extreme lengths the creator takes to maintain his dominance online, treating video production more like a data-driven business than entertainment.

Wired reports on Maka, a new streaming platform for children built to counter the flood of low-quality AI-generated videos aimed at young viewers. The article argues that kids' online content has become deeply broken, with algorithm-driven slop crowding out quality programming, and positions Maka as a curated alternative offering safer, human-made entertainment for children.

A new discussion asks whether consumers who regularly face discrimination from people may actually feel safer turning to AI for advice. The argument is that automated systems can feel less biased in everyday interactions than human advisers, even as researchers caution that algorithms carry their own embedded biases and risks that consumers cannot easily see.

A Dutch Green magazine essay marks twenty years of Twitter by arguing that the centralisation of the internet has handed Big Tech gatekeepers too much power over public debate. Drawing on the platform's history, it offers four lessons: small platforms feel better, free speech cannot be privatised, algorithms should not govern public discourse, and the online town square needs rebuilding on more decentralised foundations.

A detailed examination of the mathematics behind OpenAI's claim that its models can compute faster Fourier transforms is drawing attention. The analysis assesses whether the claimed speedups hold up under scrutiny and what they actually mean for algorithmic discovery, with readers debating the significance and validity of OpenAI's assertions.

Cryptography engineer Filippo Valsorda has published guidance on the right answers to adopt as systems move to post-quantum cryptography, laying out which algorithms and design choices practitioners should back. The piece is drawing attention from developers and security engineers weighing how and when to migrate encryption ahead of quantum threats.

Germany's Bundeswehr is now using artificial intelligence, with help from military intelligence, to vet applicants for signs of right-wing extremism before they are admitted. The move comes as the German armed forces face repeated scandals involving soldiers with far-right ties, and it raises questions about accuracy, privacy and how algorithmic screening of candidates will be overseen.

A new report outlines the research behind the world's fastest autonomous racing drone, explaining the engineering and AI systems that allow a drone to race at extreme speeds without a human pilot. The work highlights advances in perception, control algorithms and hardware that push autonomous flight to new limits, and it is drawing attention from robotics and drone racing communities.

The Wall Street Journal has published an opinion piece asking whether AI-generated health narratives can be trusted. The article examines the risks of relying on artificial intelligence for medical information and personal health decisions, raising questions about accuracy and accountability when algorithms interpret or communicate health data. The topic feeds into a broader global debate about AI reliability in sensitive areas like medicine.

Tensions are rising in US healthcare over the use of artificial intelligence, with insurance payers and care providers clashing over how AI is deployed. Insurers increasingly use algorithms for claims review and prior authorization, while providers argue the tools delay or deny care and add administrative burdens. Health system leaders are calling for oversight and regulation as both sides race to adopt AI.

Commentators are asking whether democratic debate can survive if artificial intelligence increasingly shapes political discourse. The concern is that AI-generated content, algorithmic amplification and synthetic voices could distort public deliberation, manipulate voters and erode trust in shared facts, raising urgent questions for elections and democratic institutions worldwide.

Singapore has rolled out a government-run dating app for public employees, using a Nobel Prize-winning matching algorithm to pair singles. The move comes as the country's birth rates hit record lows, with officials framing it as an unconventional tool to encourage marriage and family formation among civil servants.

An essay on Aeon argues that by outsourcing everyday tasks to quick technological fixes, people are losing core capacities such as sensing, navigating, remembering, walking and paying attention. The piece contends that machines and algorithms are quietly retraining human abilities to work against us. Readers are sharing it widely, debating whether technology's convenience comes at the cost of our own mental and physical skills.

A new commentary argues that the US military's push into artificial intelligence is being held back by a neglected piece of the puzzle: the networks that connect sensors, platforms and commanders. The piece contends that AI will only deliver an advantage on the battlefield if data can move reliably across resilient, secure communications, making the network itself a decisive weapon rather than mere infrastructure.

Singapore's government-run dating app reportedly relies on the Gale-Shapley stable marriage algorithm, the classic matching method also used in medical residency placements, to pair users. Commenters are discussing the unusual choice of an economics and computer science staple in a state-backed matchmaking service, with debate over whether stable matching suits romantic compatibility.