Hey! Here’s a great money making opportunity using the lottery. And it’s endorsed by Google, Apple, Yahoo, Morningstar, and Microsoft!

· Source: Statistical Modeling, Causal Inference, and Social Science · Field: Legal & Regulatory — Compliance & Risk Management, Regulatory Affairs & Government Relations · Depth: Novice, long

Summary

An analysis of "Lotto Champ," an AI-powered software claiming to predict lottery numbers and offer "personalized number suggestions" for $197, reveals a pervasive network of deceptive online endorsements. Despite statistical principles indicating lottery numbers are random and unpredictable, numerous prominent platforms like Google, MSN.com, Morningstar, Apple, and Yahoo host or promote reviews that use promotional language and include direct links to purchase the software. These reviews often appear as legitimate news or editorial content, sometimes even with "SCAM WARNING!!" in the title, only to endorse the product within the article. Google's AI overview also presents contradictory information, first stating the software identifies patterns and then acknowledging the lottery's fundamental randomness. This widespread corporate complicity in promoting a dubious product highlights a significant issue of online misinformation and potential exploitation of gambling addicts.

Key takeaway

For any professional evaluating software claims, especially those involving financial gain or "AI-powered" predictions for random events, you must critically scrutinize online reviews and endorsements. Do not assume legitimacy based solely on a major brand's hosting of content; investigate the content's nature and look for disclaimers. Your due diligence should extend to understanding the underlying statistical impossibility of claims before considering any investment, protecting your organization from endorsing or falling victim to scams.

Key insights

Deceptive online reviews for a lottery prediction tool highlight widespread corporate complicity in promoting scams.

Principles

In practice

Topics

Best for: CTO, VP of Engineering/Data, Director of AI/ML, Consultant, AI Ethicist, Policy Maker

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Editorial summary, takeaway, and curation by AIssential. Original article published by Statistical Modeling, Causal Inference, and Social Science.