In reply to Ben Tossell’s comment on “Steve Jurvetson”
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Steve Jurvetson
@dfjsteve · Partner, DFJ
@dvdrjo @bentossell The learning comes from the people, just like for Google today. So it can incorporate non-traditional medicine as well. Everything that works. Imagine it starts with a simple mobile text interface, and as the next three billion people come online in this decade, it could become enriched with imagery and diagnostic sensors in the smartphones. The proposition for the consumer is free, unbiased advice as long as they respond to the daily prompts for input on the remedies tried and the progression of symptoms through resolution. The recommendations would come from a special purpose AI (using machine learning and then deep learning) that benefits from what would become the largest data set of over-the-counter, prescription and non-traditional remedies. What actually works? What is the actual rate of adverse events over time? (This data set alone could provide enough revenue to cover the marginal cost of operation.) The vast majority of health care does not require surgery, especially in the developing world (think infectious diseases and nutrition), but when it is required, the system could help point people to the specialist they need. The service would be offered in all languages with voice/text conversion for the illiterate. Regional epidemiologic patterns and proactive warnings would naturally follow as it becomes a trusted, life-saving advisor. As it scales, it could become a powerful distribution channel for generic drugs, priced at a small fixed margin over manufacturing cost. Since the system is the trusted advisor, the brand of the drug would be anonymous and there is no sales or marketing expense to reach this large customer base.
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