A delegation of members of the European Economic and Social Committee (EESC) visited three Finnish technological hubs to assess the potential benefits and dangers of artificial intelligence for our society. They stressed that all future developments must encompass three pillars: product safety, consumer trust, and solidarity in health and social care. Artificial intelligence applications can increase people's wellbeing, but the potential risks need to be taken seriously. The products that are emerging as a result of new technologies and the digital revolution are in general extremely helpful and can have a wide range of uses in all areas of our lives, from dispensing medicines to curing loneliness. However, they need to be handled with care, as they are not always as straightforward as they may seem.

A Polish start-up has developed the first application in a suite of artificial intelligence (AI) tools dedicated to crop monitoring, yield optimization and management of outdoor hemp fields. "We'll be able to accurately predict when flowers will be perfect for a harvest. That's important not only because cannabinoids content can drop more than 35% if collected too late, but it's also critical from a logistics point of view," said Marcin Marczak, CEO at the developer, Green Cube Solutions. "With the limitations on available equipment, good planning is the key to a successful harvest." The technology being developed by Łódź-based Green Cube is an "integrated end-to-end platform that will support farmers from soil preparation through harvest and up to product distribution," Marczak said.

Me: "Alexa, tell me what will happen in 2020." Amazon AI: "Here's what I found on Wikipedia: The 2020 UEFA European Football Championship…[continues to read from Wikipedia]" Me: "Alexa, give me a prediction for 2020." Amazon AI: "The universe has not revealed the answer to me." Well, some slight improvement over last year's responses, when Alexa's answer to the first question was "Do you want to open'this day in history'?" As for the universe, it is an open book for the 120 senior executives featured here, all involved with AI, delivering 2020 predictions for a wide range of topics: Autonomous vehicles, deepfakes, small data, voice and natural language processing, human and augmented intelligence, bias and explainability, edge and IoT processing, and many promising applications of artificial intelligence and machine learning technologies and tools. And there will be even more 2020 AI predictions, in a second installment to be posted here later this month. "Vehicle AI is going to be ...

What do these topics have in common? The answer can be found in machine learning research at Binghamton University. Dana Bani-Hani, a doctoral student studying industrial and systems engineering, has spent the past few years teaching machines how to read data sets in any industry. The system she coded, called a Recursive General Regression Neural Network Oracle (R-GRNN Oracle), takes data inputs and creates prediction outputs. Classification models are not new in data science and analytics, but what Bani-Hani created goes beyond the basics.

Researchers at the Yonsei University of Seoul have developed a new type of robotic contact lens that can be recharged wirelessly and which could bring a wide variety of futuristic uses for contact lenses one step closer to reality. The new devices are built around a circular translucent antenna and super capacitor system that can receive continual power without needing to be plugged in to an external power source. These experimental new contact lenses will also be able to draw electricity without raising the temperature of the lens, eliminating a potential long-term cause of harm to wearers and the device itself. According to a report from Yonhap News Agency, because the lenses are completely self-enclosed they can be maintained with standard contact solutions without any risk of degradation. The team used soft contact lens material instead of rigid material to ensure the tools could be used in as wide a variety of circumstances as possible.

From news outlets to social media sites, there are numerous places that spread fake news, but a study has uncovered a new source – you. Researchers found that people will misremember numerical statistics on a controversial topic in a way that fits their own commonly held beliefs. For example, when people were shown that the number of Mexican immigrants in the United States declined recently during the study--which is true but goes against many people's beliefs--they tended to remember the opposite. And the team also found that as people pass along this misinformation, the numbers can become further and further from the truth. The study was conducted by a team at Ohio State University, who carried out two studies to investigate how people perceive and spread fake news.

Artificial intelligence and machine learning (AI/ML) are increasingly transforming the healthcare sector. From spotting malignant tumours to reading CT scans and mammograms, AI/ML-based technology is faster and more accurate than traditional devices – or even the best doctors. But along with the benefits come new risks and regulatory challenges. In their latest article Algorithms on regulatory lockdown in medicine recently published in Science, Boris Babic, INSEAD Assistant Professor of Decision Sciences; Theodoros Evgeniou, INSEAD Professor of Decision Sciences and Technology Management; Sara Gerke, Research Fellow at Harvard Law School's Petrie-Flom Center for Health Law Policy, Biotechnology, and Bioethics; and I. Glenn Cohen, Professor at Harvard Law School and Faculty Director at the Petrie-Flom Center look at the new challenges facing regulators as they navigate the unfamiliar pathways of AI/ML. They consider the questions: What new risks do we face as AI/ML devices are developed and implemented?

The mobility revolution may have the potential to transform cities, but in the short term the rise in ride-hailing apps, bike sharing, and electric scooters is giving many local officials fits. A healthy dose of data and machine learning may help get this movement back on track. That's the bet that San Francisco-based StreetLight Data is making. The company is helping cities harness the explosion of data being generated by everything from smart city sensors to mobile phones to new transportation modes, in a bid to reinvent urban planning. As cities groan under rising populations and pollution, making more effective use of data could be the key to making them habitable over the long run.

Philips announces the launch of IntelliSpace AI Workflow Suite to enable healthcare providers to seamlessly integrate AI applications into the imaging workflow. Part of Philips' new enterprise imaging informatics solution, the comprehensive AI workflow platform provides a full suite of applications for integration and centralized workflow management of AI algorithms, delivering structured results wherever they're needed across the healthcare enterprise. Partners at launch include Aidoc, MaxQ AI, Quibim, Riverain Technologies and Zebra Medical. IntelliSpace AI Workflow Suite was unveiled at the 2019 Radiological Society of North America Annual Meeting (RSNA). Leiden University Medical Center (LUMC) in the Netherlands recently signed an agreement to be the first healthcare provider to install the platform.

Kartik Talamadupula is a research staff member at IBM's T.J. Watson Research Center in Yorktown Heights, New York in the AI Science - Reasoning group in IBM Research AI. His research interests lie in the field of Automated Planning, within the wider umbrella of Artificial Intelligence (AI), and in examining the issues inherent in using planning and reasoning technologies as mediators in human-machine teams. He also has research interests in reinforcement learning, conversation and dialog systems, crowdsourcing/human computation, AI for IoT, and information retrieval on social media (specifically Twitter). He received his Ph.D. in Computer Science in Fall 2014 from Arizona State University, where he worked on extending the frontiers of AI planning methods and technologies. His research focused on understanding, analyzing, and extending the role that automated planners can play as part of integrated AI systems that interact directly and cooperatively with humans.