In scientific research, plagiarism used to be a big problem. Before the advent of free and accessible plagiarism detection tools, people would actually steal the work of their peers and publish it in their name.
In the first part here, I discussed missing, outdated and unobserved data, data that is costly to produce, as well as dirty, unbalanced and unstructured… Read More »15 Data Issues and How to Fix Them – Second Part
A graph with five billion people (nearly everyone on the Internet) brings up both ethical questions and opportunities.
The media has brainwashed us into thinking of AGI as something akin to the ‘Terminator’ But when (and if) AGI comes – what would it… Read More »When AGI comes – will you recognise it?
With great power comes even greater responsibility: AI responsibility to be specific. Organizations, regulators, and data practitioners can all get behind the concept of Responsible… Read More »DSC Podcast Series: Responsible AI Frameworks: An inclusive Future for All
In this latest Data Science Central webinar, meet Shadow IT’s younger sibling. Shadow AI is the result of one-off AI initiatives inside organizations, where siloed… Read More »DSC Webinar Series: Shadow AI, the Silent Killer of Deep Learning Productivity
