This chapter discusses several key directions such as data analytics in cyberphysical systems, multidomain mining, machine Learning concepts such as deep learning, generative adversarial networks, and challenges of model reuse. Last but not the least, the chapter closes with thoughts on ethical thinking in the data analytics process.

Novel, largely artificial-intelligence-driven technologies have become more widely accessible in recent years. This, combined with the rising dominance of social media as a primary source of news and the “weaponization” of information for political and other purposes, has led to increases in the forgery and manipulation of the evidential basis of factual claims. How easy is it for us to know when the evidentials that we rely upon to assess something as “fact” have been undermined? This chapter examines different types of evidential forgery and manipulation and describes the technological, social, and cognitive challenges we face in identifying these undermined evidentials. The chapter also explores what happens if we do become aware that the evidentiary underpinnings of our facts might be untrustworthy, and asks what threat this uncertainty poses to the epistemic foundations of societal trusting relations.