You browse an e-commerce site on your mobile device, looking for a pair of shoes. Then, with every swipe on your phone, you see ads from other retailers offering you shoes, shoes and more shoes. Are you flattered that the retailer shared your session cookie with third parties? Or do you shake your head, annoyed that these ads are following you everywhere? You visit an online retailer and can't find what you're looking for.
Mumbai: The financial sector in India is driving investments into chatbots and artificial intelligence (AI) to augment customer service, but bankers are convinced that there would not be job losses as these new tools will only complement staff. When it comes to AI it is not upstarts but big guns of banking with resources, which are driving investments. State Bank of India (SBI) is working with IBM to make use of Watson -- an answering computer software to assist staff and employees. HDFC Bank has tied up with artificial intelligence firm Niki (funded by Ratan Tata and Ronnie Screwvala) to bring in conversational banking. Last week, Yes Bank partnered Payjo to launch AI-led digital initiatives.
Artificial Intelligence ("AI") swallows vast troves of data, so, as its definition suggests, it enables "the capability of a machine to imitate intelligent human behavior."1 Much like humans learn over time by exposure to different experiences and new information, AI systems can be fed enough data so that they can eventually draw conclusions and make inferences. Given AI's data diet, it is saddled with a host of privacy regulations, which vary depending on the nature of the data and its uses. This article highlights three compliance tensions between AI and the European privacy regime, the General Data Protection Regulation ("GDPR"), which contains various privacy-related principles for how personal data must be processed and provides certain data subject rights. With GDPR fines reaching as high as 4 percent of annual global turnover, or 20 million euros (whichever is higher), carriers insuring them should endeavor to understand these complex risks.
Beyond AGI is where things get really exciting and may perhaps present a slightly existential challenge for humanity--artificial superintelligence (ASI). Goertzel said, "Artificial superintelligence is the next step beyond general intelligence. Humans currently have more general intelligence than the software products that are commercially available right now. But humans are by no means the most generally intelligent possible system. I think as AI advances further and further, you're going to see AI as tremendously smarter than people much as we're much smarter than monkeys, rats or bugs. But I mean, to get from where we are now with narrow AI, to AGI, and then to artificial superintelligence, we need to go through quite a series of practical steps."
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Organizations are increasingly looking to adopt blockchain technologies for alternative data storage. And with heaps of data distributed across blockchain ledgers, the need for data analytics with AI is growing. The combination of AI and blockchain is fueling the onset of the "Fourth Industrial Revolution" by reinventing economics and information exchange. From healthcare to government, the potent combination of both AI and blockchain is slowly but surely transforming industries. Google DeepMind is developing an "auditing system for healthcare data".
Global payments unicorn Adyen is looking into how artificial intelligence can boost its payments offering, highlighting how the tech can boost the industry as a whole. The Dutch FinTech company went public last year after having raised a massive $250m Series B round in 2014, the biggest deal raised by a FinTech company in the Netherlands between 2014 and the third quarter of 2019. But more is to come and it seems as if AI will play a big role in Adyen's future. "The benefits of AI are real," Pieter van der Does, CEP of Adyen, told VentureBeat at the Slush technology conference in Helsinki. However, initially the tech leader was cautious about using AI.
Artificial intelligence has had a profound impact on finance. In the span of a few decades, it has made finance faster, more accessible, more profitable, and more efficient in many ways. Despite all the significant benefits made possible by financial artificial intelligence, it also presents serious risks and implications for law, business, and society. My recent article, 'Artificial Intelligence, Finance, and the Law', published in the Fordham Law Review, offers a study of those risks and implications. It provides a broad examination of the inherent risks and larger implications of financial artificial intelligence.
Artificial intelligence is coming for America's high-paid professions as it creates winners and losers across the labor market like never before. White-collar jobs and better-educated occupations along with production workers are among the most susceptible to AI's spread into the economy, according to a Brookings Institution report Wednesday that draws on a new analysis of patent data by a Stanford University economist. "Just as the impacts of robotics and software tend to be sizable and negative on exposed middle- and low-skill occupations, so AI's inroads are projected to negatively impact higher-skill occupations," researchers Mark Muro, Jacob Whiton and Robert Maxim wrote. Workers with graduate or professional degrees will be almost four times as exposed to AI as workers with just a high school degree, the report showed. The researchers also concluded that AI appears most likely to affect men, prime-age and white and Asian American workers.
The use of robots in U.S. workplaces has more than doubled since the Great Recession, but the impact has hit certain areas of the country -- and segments of workers -- more than others. A recent report from The Century Foundation found Midwestern states such as Michigan, Ohio, Indiana, Illinois and Wisconsin saw the sharpest growth in robots being used in the workplace from 2009 to 2017, and these areas now have the highest levels of "robot intensity" in the country. Robot intensity refers to the number of industrial robots per 1,000 human workers. The higher the number, the more robots there are in the workplace alongside humans. Areas with the highest robot intensity are home to some of the of the biggest manufacturing industries in the country.