>blockchains introduced three new characteristics: centralized / shared control, immutable / audit trails, and native assets / exchanges.
Blockchains aren't immutable, they are just expensive to mutate.
Blockchains aren't centralized.
Blockchains didn't introduce audit trails, these have always been possible simply through having a transaction table that is only appended to. This of course does require trust in the central authority.
>(4) Leads to provenance on training/testing data & models, to improve the trustworthiness of the data & models. Data wants reputation too.
Is training set fraud really an issue in training AI?
>(1) Leads to more data, and therefore better models. >(2) Leads to qualitatively new data, and therefore qualitatively new models. >(3) Allows for shared control of AI training data & models.
The author has a poor understanding of both AI and blockchain technology[1]. Blockchains are for decentralized consensus, but it seems the author is vaguely proposing using a blockchain as a mass datastore (with ownership labels) for both training data and AI algorithms.
Of course AI is an exciting field so this means you can generate hype by implying the field of AI has yet to solve the problem of sharing data with fellow researchers until now.