Issues


Can trusted data exchanges help grow ethical AI? - IoT Agenda

#artificialintelligence

AI is transforming the world as we know it. Contextual awareness paired with AI is opening the door to many positive solutions for healthcare, environmental protection, conservation, smart cities and public safety. Enterprise AI applications also proliferate in marketing and sales, HR and recruiting, security, autonomous operations and financial services. On the other hand, the rapid advancement of AI also raises questions and concerns around data ethics, which are only beginning to be addressed. As a case in point, the New York Police Department (NYPD) has been challenged by AI bias concerns for its new crime analysis AI tool.


What jobs are affected by AI? Better-paid, better-educated workers face the most exposure

#artificialintelligence

Artificial intelligence (AI) has generated increasing interest in "future of work" discussions in recent years as the technology has achieved superhuman performance in a range of valuable tasks, ranging from manufacturing to radiology to legal contracts. With that said, though, it has been difficult to get a specific read on AI's implications on the labor market. In part because the technologies have not yet been widely adopted, previous analyses have had to rely either on case studies or subjective assessments by experts to determine which occupations might be susceptible to a takeover by AI algorithms. What's more, most research has concentrated on an undifferentiated array of "automation" technologies including robotics, software, and AI all at once. The result has been a lot of discussion--but not a lot of clarity--about AI, with prognostications that range from the utopian to the apocalyptic.


Elon Musk says Neuralink could bring A.I. 'superintelligence' to the brain

#artificialintelligence

Beyond cortical and limbic systems, the company Neuralink could add a third layer of digital superintelligence to humans and avoid artificial intelligence enslavement, its founder Elon Musk claimed Tuesday. The brain-computer linkup firm is working to treat medical conditions using its implanted chip as early as next year, but during a podcast appearance, Musk reiterated his belief that the technology could avoid some of the worst consequences of advanced machines. "It's important that Neuralink solves this problem sooner rather than later, because the point at which we have digital superintelligence, that's when we pass the singularity and things become just very uncertain," Musk said during an interview with MIT professor Lex Fridman. Musk was keen to note that the singularity, a hypothesized point where machines grow so advanced that humanity slips into an irreversible change, may not necessarily be good or bad. He did state, however, that "things become extremely unstable" after that point, which means Neuralink would need to achieve its human-brain linkup either before or not long after "to minimize the existential risk for humanity and consciousness as we know it."


Asia Times Why China will win the race for AI Opinion

#artificialintelligence

The role of the development of artificial intelligence in geopolitics usually means competition between the United States and China. While reports are inconclusive about which country will ultimately win (if this is the right term), there is a glaring shortcoming in the United States that China will largely avoid. In 2017 China accounted for 48% of global AI venture capital while the US only accounted for 38%. But only two years later the trend reversed, possibly because of headwinds from the trade war. Neither is it talent acquisition and a brain drain.


Brookings: AI will heavily affect tech and white-collar jobs

#artificialintelligence

AI is set to have a big impact on high-wage, white-collar, and tech jobs, according to a new Brookings Institution study released today. The report analyzes overlap between job descriptions and patent database text, using NLP to assign each job an exposure score. "High-tech digital services such as software publishing and computer system design -- that before had low automation susceptibility -- exhibit quite high exposure, as AI tools and applications pervade the technology sector," the report reads. The AI exposure score was created by researcher Michael Webb to predict the likelihood AI will affect certain cities, regions, occupations, industries, or demographic groups, but is not designed to determine whether that impact is positive or negative. Exposure to AI could mean that the tech will likely augment or change how certain occupations work, or it could mean a higher likelihood AI will take your job.


MIT-IBM Watson AI Lab Releases Groundbreaking Research on AI and the Future of Work - Liwaiwai

#artificialintelligence

IBM believes 100% of jobs will eventually change due to artificial intelligence, and new empirical research released last October 30 from the MIT-IBM Watson AI Lab reveals how. The research, The Future of Work: How New Technologies Are Transforming Tasks, used advanced machine learning techniques to analyze 170 million online job postings in the United States between 2010 and 2017. It shows, in the early stages of AI adoption, how tasks of individual jobs are transforming and the impact on employment and wages. "As new technologies continue to scale within businesses and across industries, it is our responsibility as innovators to understand not only the business process implications, but also the societal impact," said Martin Fleming, vice president and chief economist of IBM. "To that end, this empirical research from the MIT-IBM Watson AI Lab sheds new light on how tasks are reorganizing between people and machines as a result of AI and new technologies."


The Debate Around Thinking Capabilities of Artificial Intelligence Analytics Insight

#artificialintelligence

Artificial intelligence and machine learning processes are being utilized in more and procedures which impact our day-to-day life. From giving you more applicable advertisements to helping you pick the correct movie to watch, such tools extend from simple information matching, to progressively complex forecasts. What's more, those varying uses can have critical implications on their utility and advantage pushing ahead. The key interesting point when taking a look at such matches is the dataset being utilized to foresee the ultimate result. Machines are not ready to'think' like an individual, they don't utilize individual judgment.


The Age of Thinking Machines

#artificialintelligence

We live in the greatest time in human history. Only 200 years ago, for most Europeans, life was a struggle rather than a pleasure. Without antibiotics and hospitals, every infection was fatal. There was only a small elite of citizens who lived in the cities in relative prosperity. Freedom of opinion, human and civil rights were far away. Voting rights and decision-making were reserved for a class consisting of nobility, clergy, the military and rich citizens. The interests of the general population were virtually ignored.


AI & Society – A Responsible View

#artificialintelligence

Since I spoke at techUK's Digital Ethics 2018 conference the conversation on AI has continued to grow. Research that we recently conducted showed that UK organisations have been increasing their adoption of AI technologies over the past year. The number of companies who now state they have an AI strategy in place has more than doubled – from 11% in 2018 to 24% today, with over half of the organisations reported to be using AI to some degree, indicating that AI is increasingly becoming more accessible. The rise in AI technologies creates more urgency for organisations to understand the implications of AI empowered decision making and how to ensure AI is being used responsibly. However, many UK leaders lack an understanding of how AI can be used in a fair, responsible and effective way with two-thirds (63%) not knowing how AI systems reach conclusions.


AI's ethics problem: Abstractions everywhere but where are the rules?

#artificialintelligence

Machines that make decisions about us: what could possibly go wrong? Essays, speeches, seminars pose that question year after year as artificial intelligence research makes stunning advances. Baked-in biases in algorithms are only one of many issues as a result. Jonathan Shaw, managing editor, Harvard Magazine, wrote earlier this year: "Artificial intelligence can aggregate and assess vast quantities of data that are sometimes beyond human capacity to analyze unaided, thereby enabling AI to make hiring recommendations, determine in seconds the creditworthiness of loan applicants, and predict the chances that criminals will re-offend." Again, what could possibly go wrong?