Part of my continuous learning, collaboration, and contribution is a comprehensive resource list, updated monthly. It includes four categories: strategic thinking, practical advice, product reviews, and a social context.
You can’t evaluate AI solutions without understanding the basics of practical machine learning and predictive analytics. You don’t have to be a data scientist for that. It’s like driving a car – you don’t need to be a mechanical engineer to buy or drive your car.
Employees and candidates will judge employers, in addition to Employee Experience perceptions, by employer ethics in data management, and when feeling secure, they’ll be more receptive and enthusiastic to participate and cooperate with AI and ML to influence their career path.