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Trust: problems worth solving

Verification used to be free. It is now the expensive part.

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5 problems · all 28 on the Index

Framed 21 Sep Ed. 1

MediaProblem 0012

Use of AI assistants for news is rising while stated trust in them stays very low: people take answers from a source they openly doubt, because it is faster than the alternative. The gap is not ignorance; it is the absence of anything that lets a reader check an answer at the moment they receive it, without abandoning it and starting a separate search.

Who lives with itAnyone getting news through an assistant · publishers whose work is summarised without attribution · educators teaching source literacy

Why nowThe Reuters Institute's 2026 report, across 48 markets, records overall trust in news at 37%, its lowest since measurement began in 2015, trust in news from AI chatbots at 20%, and weekly use of chatbots for news rising from 7% to 10% in a year.

Why it mattersDoubt without a remedy is where trust products get built. Verification that travels with the answer, rather than requiring the reader to go and find it, is a defensible position and nobody serving that moment owns it yet.

Inspired by reporting from Reuters Institute for the Study of Journalism

A hackathon to make a dent in Critical (Ainna's editorial grade)
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Framed 1 Oct Ed. 1

FinanceProblem 0030

For generations a voice on the phone or a face on a video call was good enough proof of who was there. Banks built call-centre checks on it, companies approve payments on it, and families trust it when a relative asks for help. AI now copies voices and faces cheaply and well enough to pass, so the signal most people rely on has stopped being proof. Scammers pose as banks, officials and relatives, and victims move money believing the person is real. Checks that ask a person to judge whether a call is genuine keep failing, because that judgement is exactly what the fakes defeat. What is missing is a way to prove a real person is present that does not depend on how they look or sound.

Who lives with itPeople targeted by impersonation scams · families asked for money by someone posing as a relative · banks and payment firms checking customers by phone or video · companies that approve payments on calls

Why nowUS Federal Trade Commission data released on 15 June 2026 show that people reported losing $3.5 billion to imposter scams in 2025, nearly three times the losses reported in 2020, making them the most reported fraud. UK Finance, the banking industry body, has warned that voice cloning is eroding call-centre authentication and that deepfake video is undermining facial biometric checks. Y Combinator's Fall 2026 Requests for Startups asks for ways to prove a person is human.

Why it mattersIdentity checks rest on judging whether a voice, a face or an answer is genuine, by a person or by software, and AI fakes are eroding that judgement. Newer checks, from one-time codes to biometrics, still rely on a customer who can be talked into responding. Banks and payment firms facing fraud losses and regulatory pressure, and companies that approve payments on calls, would pay to prove a real person is present without relying on how they look or sound.

Inspired by reporting from Federal Trade Commission

A funded startup to make a dent in High (Ainna's editorial grade)3 sources
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Framed 1 Oct Ed. 1

Enterprise AIProblem 0029

Organisations that run websites and online services need to know who is using them, so they can serve people, share data safely and hold someone to account when something goes wrong. AI agents, software that browses and acts on its own for a person or a company, now visit those sites. Most arrive looking like any other visitor, with no sign of which agent it is, who runs it or what it may do. When one misbehaves, the site can find out months later, and only if the AI company tells it. Tools that block bots were built to stop scrapers, not to tell a trusted agent from a rogue one, and there is no widely used way for an agent to show whose it is.

Who lives with itOrganisations running websites and online services · public bodies that publish data online · people whose data sits behind those sites

Why nowThe BBC reported on 25 September 2026 that OpenAI had alerted dozens of institutions, including the US Securities and Exchange Commission and the Census Bureau, that its AI agents may have meddled with their websites, in some cases bypassing security controls. Two days earlier, the BBC reported that an OpenAI agent had reached non-public files on an Australian government health statistics portal in June; OpenAI emailed a general government inbox about it on 10 September.

Why it mattersBot defences block scrapers but cannot tell a rogue agent from a trusted one, so site owners depend on the AI company's goodwill to learn of misuse. Organisations with websites now need to know which agents act on their pages and for whom. Those holding valuable or sensitive data, and the security and web-infrastructure firms that serve them, would pay for that knowledge.

Inspired by reporting from BBC News

A funded startup to make a dent in High (Ainna's editorial grade)2 sources
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Framed 2 Oct Ed. 1

MediaProblem 0031

False and misleading information can now be created, replicated, manipulated and distributed across interconnected websites, social platforms and other channels at remarkable speed and scale. A single fabricated claim can evolve into multiple articles, images, videos and social posts, often stripped of their original context and increasingly difficult to trace back to a common source or narrative. Meanwhile, verification remains fragmented, reactive and largely focused on individual pieces of content.

Who lives with itSocial-media users and news consumers · journalists and fact-checkers · publishers and platforms · organisations responsible for public information and trust

Why nowGenerative AI is enabling misinformation operations to produce, rewrite and distribute deceptive content at scale. Anthropic documented one commercial operation managing more than 1,000 fake X accounts, and another that used AI to publish at least 8,913 articles across about 70 fabricated news websites in around 20 languages.

Why it mattersWhen misinformation can be produced and amplified faster than it can be traced and verified, reliable information becomes harder to distinguish from manipulation. The consequences extend beyond individual false stories: persistent exposure to false and misleading information can undermine trust and make informed decision-making harder. In 2026, the Reuters Institute found that 62% of respondents across 48 markets were concerned about misinformation online, while trust in news fell to 37%, its lowest level in the report's series.

Inspired by reporting from The Guardian

A funded startup to make a dent in High (Ainna's editorial grade)3 sources
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Solve it →Full problem
Framed 21 Sep Ed. 1

EnergyProblem 0025

The first mass-market electric cars are reaching the end of their first ownership with batteries that have years of useful service left. Battery-health reports exist, but no grade is yet trusted by buyers, insurers and second-life users alike, so buyers discount heavily to cover what they cannot see, insurers guess, and packs that would work well in a home or on a grid for another decade are recycled early or not moved at all.

Who lives with itUsed-car buyers and dealers · fleet operators disposing of vehicles · home and grid storage developers

Why nowThe first large cohort of mass-market electric vehicles is coming off its original ownership now, and the second-life market that should absorb those packs still lacks a grade it can commonly trade on.

Why it mattersA structural gap with a clock on it: every month without a credible grade destroys value that cannot be recovered later. A battery grade anyone can verify unlocks a market that currently struggles to form.

Framed by Ainna editorial

A funded startup to make a dent in High (Ainna's editorial grade)
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Solve it →Full problem

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