Description: Beginning in 2020, Wayne Luxon, a 43-year-old self-employed father of four from Taunton, Somerset, reportedly lost £140,000 after responding to a Facebook advertisement using a purportedly AI-generated Martin Lewis deepfake to promote cryptocurrency investment. Luxon said he was directed to a clone platform where he made additional payments after seeing fictitious gains, and later paid purported tax fees before the account balance fell to zero.
Editor Notes: Timeline notes: Wayne Luxon reportedly first encountered the purported deepfake Martin Lewis cryptocurrency advert on Facebook in 2020; 01/01/2020 is an approximate incident date. The case was reported on 05/31/2026 in coverage of group legal action against Meta over scam advertisements. The incident ID was created 05/31/2026. See also Incident 1268: Meta's Automated Ad and Targeting Systems Reportedly Enabled Large-Scale Fraud Revenue.
Entities
View all entitiesAlleged: Voice cloning technology developers and Deepfake technology developers developed an AI system deployed by Unknown cryptocurrency scammers and Scammers, which harmed Wayne Luxon , Investors , Epistemic integrity , Cryptocurrency scam victims and Cryptocurrency investors.
Alleged implicated AI systems: Voice cloning technology , Social media platforms , Meta , Facebook , Deepfake technology , Cryptocurrency scam platforms and Clone investment websites
Incident Stats
Incident ID
1509
Report Count
2
Incident Date
2020-01-01
Editors
Daniel Atherton
Incident Reports
Reports Timeline
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A dad who lost £140,000 after falling for a deepfake Martin Lewis video on Facebook has slammed the social media giant for failing to 'stop' scams.
Wayne Luxon, from Taunton in Somerset, said he went to a "dark place" after he was conned in…
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The owner of Facebook and Instagram faces a multi-billion pound group legal action from British consumers who accuse it of enabling scam adverts which left them facing financial ruin.
Social media platforms are estimated to have raked in mo…
Variants
A "variant" is an AI incident similar to a known case—it has the same causes, harms, and AI system. Instead of listing it separately, we group it under the first reported incident. Unlike other incidents, variants do not need to have been reported outside the AIID. Learn more from the research paper.
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