How to improve verifiability of AI claims - Datascience.aero

From the perspective of technology companies, one of the greatest challenges to developing cutting edge technology is ensuring that the innovation budget receives significant recognition among users, regulators and other stakeholders. Receiving recognition sometimes means publishing papers in peer-reviewed magazines, presenting in conferences and preparing press releases that showcase the advancements in technology. Though companies can sometimes grow to be very "optimistic" of perceived progress, some claims of progress lack the necessary proofs to ensure that developments are relevant. While AI potential applications can be varied and diverse, making sure that a system is sound, scalable, uses available datasets and can perform in a real-world environment is a daunting task. Sometimes the proposed approaches fail in their methodology as the data is simply not available to support industrialisation of the system; or, the system is not safe and confidentiality concerns remain about how the data will be used.