This is the sixth, and final episode in a series dedicated to all things A.I. In this episode, Tae Royle, Head of Digital Products APAC from Ashurst Advance Digital is joined by Tara Waters, Partner and Head of Ashurst Advance Digital. This is the sixth and final episode in a series dedicated to all things Artificial Intelligence. My name is Tae Royle head of digital products from Ashurst did that digital and today I'm joined by Tara Waters partner and head of Ashurst Advanced Digital based out of our London office. Naturally we come to the question of what's next? In Lewis Carroll's second novel, Alice enters Wonderland by climbing through a mirror.
Artificial intelligence is already impacting virtually every industry and every human being. This incredible technology has brought many good and questionable things into our lives, and it will create an even bigger impact in the next two decades. According to Ray Kurzweil, one of the most-known futurists, computers will have the same level of intelligence as humans by 2029. Kurzweil stated to Futurism, "2029 is the consistent date I have predicted for when an AI will pass a valid Turing test and therefore achieve human levels of intelligence. I have set the date 2045 for the'Singularity' which is when we will multiply our effective intelligence a billion fold by merging with the intelligence we have created."
Three groups focused on increasing diversity in artificial intelligence say they will no longer take funding from Google. In a joint statement released Monday, Black in AI, Queer in AI, and Widening NLP said they acted to protest Google's treatment of its former ethical AI team leaders Timnit Gebru and Margaret Mitchell, as well as former recruiter April Christina Curley, a Black queer woman. "The potential for AI technologies to cause particular harm to members of our communities weighs heavily on our organizations," the statement reads. "Google's actions in the last few months have inflicted tremendous harms that have reverberated throughout our entire community. They not only have caused damage but set a dangerous precedent for what type of research, advocacy, and retaliation is permissible in our community."
"Trust is a must," she said. "The EU is spearheading the development of new global norms to make sure AI can be trusted. By setting the standards, we can pave the way to ethical technology worldwide." Any fast-moving technology is likely to create mistrust, but Vestager and her colleagues decreed that those in power should do more to tame AI, partly by using such systems more responsibly and being clearer about how these work. The landmark legislation – designed to "guarantee the safety and fundamental rights of people and businesses, while strengthening AI uptake, investment and innovation" – encourages firms to embrace so-called explainable AI.
Amita Kapoor is an Associate Professor in the Department of Electronics, SRCASW, University of Delhi and has been actively teaching neural networks and artificial intelligence for the last 20 years. She completed her masters in Electronics in 1996 and Ph.D. in 2011, during Ph.D. she was awarded a prestigious DAAD fellowship to pursue a part of her research work in Karlsruhe Institute of Technology, Karlsruhe, Germany. She was awarded the Best Presentation Award at the Photonics 2008 international conference. She is an active member of ACM, AAAI, IEEE, and INNS. She has co-authored four books including the best-selling book "Deep learning with TensorFlow2 and Keras" with Packt Publications.
When we imagine the future of AI, we may think of the fiction we see in cinema: highly advanced robots that can mimic humans so well as to be indistinguishable from them. It is true that the ability to quickly learn, process, and analyze information to make decisions is a key feature of artificial intelligence. But what most of us have come to know as AI actually belongs to a subdiscipline called machine learning. Artificial intelligence has become a catch-all term for several algorithmic fields of mathematics and computer science. There are some key differences between them that are important to understand to maximize their advancement potential.
In the present paper we present the potential of Explainable Artificial Intelligence methods for decision-support in medical image analysis scenarios. With three types of explainable methods applied to the same medical image data set our aim was to improve the comprehensibility of the decisions provided by the Convolutional Neural Network (CNN). The visual explanations were provided on in-vivo gastral images obtained from a Video capsule endoscopy (VCE), with the goal of increasing the health professionals' trust in the black box predictions. We implemented two post-hoc interpretable machine learning methods LIME and SHAP and the alternative explanation approach CIU, centered on the Contextual Value and Utility (CIU). The produced explanations were evaluated using human evaluation.
Mumbai (Maharashtra) [India], May 7 (ANI/NewsVoir): Since the dawn of the 2000s, Artificial Intelligence (AI) has been making waves through its penetration into various sectors. While AI helps increase efficiency and speed in a system, the lack of feedback when faced with errors has been a glaring concern. Recently developed Explainable Artificial Intelligence (XAI) technology tackles this issue by analyzing data to provide users with explanations for given issues and activities. Utilizing this technology to create investment strategies, Elystar aims to increase net returns by reducing machine/AI-made errors and thereby successfully leveraging the superior insights provided by AI. "Artificial Intelligence in finance is a relatively new concept that is still being explored and experimented upon. While few of the firms experimenting are sparingly using it for short-term trading, we have spent the past 15 months developing models to use it for long-term investments. One simple way to look at this concept is to compare it with Microsoft Excel. While Excel is used in different fields and by different people, it is used in various ways and forms. Similarly, AI has a number of variations in which it can be utilized, so no two approaches may be completely the same. AI not only helps us scale and analyze data rapidly, but the integration of Explainable AI allows us to understand and eliminate unwarranted biases to create a sound investment strategy," said Dr Satya Gautam Vadlamudi, Founder and CEO of Elystar.
It was December 2020, and she was being invited into a pilot program providing guaranteed income--a direct cash transfer with no strings attached. For Softky, it was a lifeline. "For the first time in a long time, I felt like I could … take a deep breath, start saving, and see myself in the future," she says. The idea of "just giving people money" has been in and out of the news since becoming a favored cause for many high-profile Silicon Valley entrepreneurs, including Twitter's Jack Dorsey, Facebook cofounders Mark Zuckerberg and (separately) Chris Hughes, and Singularity University's Peter Diamandis. They proposed a universal basic income as a solution to the job losses and social conflict that would be wrought by automation and artificial intelligence--the very technologies their own companies create.