The growth potential of the data economy is mind-blowing. In Europe alone, the figures and forecasts are eye-catching, to say the least. The European Commission expects the value of the data economy to rise to €829 billion by 2025, up from €301 billion in 2018. Focusing on the headline economic figures alone overlooks the enormous potential to use data to create lasting social change and improve the personal and professional lives of millions of European citizens. The term digital economy is a catch-all for a wide range of digital transformation activities.

On Tuesday, a number of AI researchers, ethicists, data scientists, and social scientists released a blog post arguing that academic researchers should stop pursuing research that endeavors to predict the likelihood that an individual will commit a criminal act, as based upon variables like crime statistics and facial scans. The blog post was authored by the Coalition for Critical Technology, who argued that the utilization of such algorithms perpetuates a cycle of prejudice against minorities. Many studies of the efficacy of face recognition and predictive policing algorithms find that the algorithms tend to judge minorities more harshly, which the authors of the blog post argue is due to the inequities in the criminal justice system. The justice system produces biased data, and therefore the algorithms trained on this data propagate those biases, the Coalition for Critical Technology argues. The coalition argues that the very notion of "criminality" is often based on race, and therefore research done on these technologies assumes the neutrality of the algorithms when in truth no such neutrality exists.

Moscow City Hall has been instructed to determine the conditions, requirements and procedure for the development, creation, introduction and implementation of artificial intelligence technologies, as well as the cases and procedures for using the results of the application of artificial intelligence. It is expected that large IT companies using artificial intelligence in the field of medicine, urban infrastructure, face recognition and other uses will take part in the experiment. The Law separately outlines certain provisions relating to the storage and processing of personal data that will be obtained during the experiment. As a result, the Law makes it possible to use the previously anonymised personal data of individuals participating in the experiment to increase the effectiveness of the state or municipal government. However, the Law specifically establishes that such personal data can only be transferred to participants in the experiment and must be stored in Moscow.

Adopting AI can affect not just your workers but how you deal with privacy and discrimination issues. As humans become more reliant on machines to make processes more efficient and inform their decisions, the potential for a conflict between artificial intelligence and human rights has emerged. If left unchecked, artificial intelligence can create inequality and can even be used to actively deny human rights across the globe. However, if used optimally, AI can enhance human rights, increase shared prosperity, and create a better future for us all. It is ultimately up to businesses to carefully consider the opportunities new technologies provide and how they can best leverage these opportunities while being conscious of the impact on human rights.

THuMP is a multi-disciplinary project, with the ambitious goal of advancing the state-of-the-art in trustworthy human-AI decision-support systems. ThUMP will address the technical challenges involved in creating explainable AI (XAI) systems, with a focus on Visualization for Explainable Planning and Argumentation, so that people using the system can better understand the rationale behind and trust suggestions made by an AI system. This project is conducted in collaboration with three project partners: Schlumberger and Save the Children, which provide use cases for the project, and a law firm whowill cooperate in considering legal implications of enhancing machines with transparency and the ability to explain. The candidate will be responsible for conducting research around the interfaces required to support explainability in the context of decision making in human-machine partnerships. Tasks will involve designing new visual layouts, building the interaction infrastructure for the project, developing a prototype interface for communicating with users, designing and conducting experiments with human subjects based on the use cases that will be co-created with the project partners.

Technology, media and telecoms (TMT) regulators will ponder rather than act on AI. Increased use of AI to generate deepfakes in the US presidential campaign may be the catalyst for substantive regulation. Debate regarding access to, and ownership of, data will continue with little regulatory change. For many industries, the focus will remain on operational efficiency. AI-based virtual assistants will gain significant traction.

Adopting AI can affect not just your workers but how you deal with privacy and discrimination issues. As humans become more reliant on machines to make processes more efficient and inform their decisions, the potential for a conflict between artificial intelligence and human rights has emerged. If left unchecked, artificial intelligence can create inequality and can even be used to actively deny human rights across the globe. However, if used optimally, AI can enhance human rights, increase shared prosperity, and create a better future for us all. It is ultimately up to businesses to carefully consider the opportunities new technologies provide and how they can best leverage these opportunities while being conscious of the impact on human rights.

BPU Holdings is a global company, headquartered in Korea that pioneers in the development of Artificial Emotional Intelligence (AEI). The mission of the company is to generate the most advanced, secure usable, and innovative Artificial Emotional Intelligence technology in the world. BPU has developed the first Artificial Emotional Intelligent (AEI) platform -- AEI Framework, which emulates how people think and feel. BPU improves the human condition by offering rigorous tools to improve emotional intelligence. Tracking and handling emotions enable the management of professional and interpersonal relationships, empathetically and judiciously.

I've spent the last few months preparing for and applying for data science jobs. It's possible the data science world may reject me and my lack of both experience and a credential above a bachelors degree, in which case I'll do something else. Regardless of what lies in store for my future, I think I've gotten a good grasp of the mindset underlying machine learning and how it differs from traditional statistics, so I thought I'd write about it for those who have a similar background to me considering a similar move.1 This post is geared toward people who are excellent at statistics but don't really "get" machine learning and want to understand the gist of it in about 15 minutes of reading. If you have a traditional academic stats backgrounds (be it econometrics, biostatistics, psychometrics, etc.), there are two good reasons to learn more about data science: The world of data science is, in many ways, hiding in plain sight from the more academically-minded quantitative disciplines.

OTTAWA, ON, June 15, 2020 /CNW/ - Kinaxis Inc. (TSX: KXS), the authority in driving agility for fast, confident decision-making in an unpredictable world, has signed a definitive agreement to acquire Toronto-based Rubikloud, a disruptive, emerging provider of AI solutions that automate supply chain prescriptive analytics and decision-making in the retail and consumer packaged goods (CPG) industries. Globally-recognized retailers and CPG manufacturers in the health and beauty, household and grocery segments use Rubikloud's AI-based products today. Their offerings include demand forecasting and automation to manage and optimize trade promotions, pricing and assortment to drive product demand and dramatically improve financial results. Kinaxis will enhance RapidResponse's demand planning capabilities with the Rubikloud offerings, anticipating initial opportunities in the company's rapidly-growing CPG customer base and over time for other industries such as life sciences. The acquisition also offers Kinaxis a springboard into the enterprise retail industry.