The answer: both suffer from a "truthiness" problem. Truthiness is a term coined by Stephen Colbert to describe the tactic of weaving facts into a false narrative. Conspiracy theories like QAnon rely on truthiness, using individual data points to reach wild and untrue conclusions like ISIS was created by the CIA or a hidden Deep State runs the U.S. government. Like it or not, human beings are highly susceptible to truthiness: research indicates that 50% of Americans believe in at least one conspiracy theory. The AI business also suffers from a "truthy" belief: that when black box algorithms are used to make high-stakes decisions--like who gets approved for a loan, a job interview, or even an organ transplant--the fact that we don't know HOW these algorithms reach their decisions is not a problem so long as an AI developer can "explain" a model's reasoning.

In 2019, as the Department of Defense considered adopting AI ethics principles, the Defense Innovation Unit held a series of meetings across the U.S. to gather opinions from experts and the public. At one such meeting in Silicon Valley, Stanford University professor Herb Lin argued that he was concerned about people trusting AI too easily and said any application of AI should include a confidence score indicating the algorithm's degree of certainty. "AI systems should not only be the best possible. Sometimes they should say'I have no idea what I'm doing here, don't trust me.' That's going to be really important," he said. The concern Lin raised is an important one: People can be manipulated by artificial intelligence, with cute robots a classic example of the human tendency to trust machines.

Researchers at Ulster University have published the results of their work on developing the first biological neural network model equipped with self-awareness, a form of metacognition. This breakthrough research could have important implications in providing insights into brain disorders related to distorted self-awareness, or the development of self-aware artificial intelligence (AI) machines. The Intelligent Systems Research Centre (ISRC) at Ulster University's Magee campus in Derry is the site of this pioneering research, which was recently published in the prestigious journal, Nature Communications. For years, researchers at ISRC have been working on developing and applying biologically inspired algorithms that go beyond standard AI algorithms, leveraging the solutions nature provided to solving complex problems in computing and AI. This includes utilising knowledge in brain sciences towards the development of superior and efficient computer algorithms or machines.

Machine Learning is one of the most sought after skills these days. If you are a data scientist, then you need to be good at Machine Learning – no two ways about it. As part of DataFest 2017, we organized various skill tests so that data scientists can assess themselves on these critical skills. These tests included Machine Learning, Deep Learning, Time Series problems and Probability. This article will lay out the solutions to the machine learning skill test. If you missed out on any of the above skill tests, you can still check out the questions and answers through the articles linked above. In Machine Learning skill test, more than 1350 people registered for the test.