Adorable Japanese robot. China + AI. BP turns to Big Data. http://cognitionx.com/news-briefing/.
According to a recent report from Northstar and ARM on the present and future of AI, 71% of respondents (4,000 global consumers) thought that within 5 years, AI will have a noticeable impact on our daily life.
To find out which specific industries will be most affected, we look to the latest reports from McKinsey, PwC, and Accenture for some differing opinions.
Business executives realise just how ubiquitous AI will be, with more than 73% of CEOs predicting that AI will play a “key role” in their business’s future (IBM).
Dr Joanna Bryson says that since her paper
on bias in AI came out “it’s been evident that people are surprised that machines can be biased.” This, she argues, is rooted in the fact that they mistake computation for mathematics, which is by definition true and eternal.
Bias: unintentionally uploading the implicit human biases that pervade our culture
Solution: fix our culture, or at least compensate for it
Bias: poorly-selected training data
Solution: adequately testing system
Bias: programmers/institutions with nefarious motives
Solution: all algorithms that affect people’s lives should be subject to audit.
The device, created by the Japan Aerospace Exploration Agency (JAXA), was delivered to the International Space Station on June 4, 2017, and now JAXA is releasing its first video and images.
The purpose of Int-Ball is to give scientists on the ground the ability to remotely capture images and video, via a robot that can move autonomously around in space and capture both moving and still imagery. The 3D-printed drone offer real-time monitoring for “flight controllers and researchers on the ground,” according to JAXA, and the media it gathers can also be fed back to ISS crew.
Join Science:Disrupt for their London Session at Entrepreneur First, where they will tackle the rapidly changing landscape of Advanced Computing! They’ll be diving into cryptography and cybersecurity, building meaningful applications on the blockchain, the disruptive force of quantum technologies….and of course anything else you want to add in the Q&A panel!
To understand why China is so well placed, consider the inputs needed for AI. Of the two most basic, computing power and capital, it has an abundance. In addition,
Yet it is two other resources that truly make China a promised land for AI. One is research talent. As well as strong skills in maths, the country has a tradition in language and translation research, says Harry Shum, who leads Microsoft’s AI efforts. The second advantage for China is data, AI’s most important ingredient. In the past, software and digital products mostly obeyed rules laid down in code, giving an edge to those countries with the best coders. With the advent of deep-learning algorithms, such rules are increasingly based on patterns extracted from reams of data. The more data are available, the more algorithms can learn and the smarter AI offerings will be.
Cathy O’Neil, data scientist and author of Weapons of Math Destruction, has a 4-layer hierarchy when it comes to bad algorithms. She argues that “we need to demand evidence that algorithms with the potential to harm us be shown to be acting fairly, legally, and consistently. When we find problems, we need to enforce our laws with sufficiently hefty fines that companies don’t find it
profitable to cheat in the first place”.
unintentional problems that reflect cultural biases
algorithms that go bad through neglect
nasty but legal algorithms
intentionally nefarious and sometimes outright illegal algorithms
According to new IBM research, more than 73% of CEOs predict that cognitive computing, or AI, technologies will play a “key role” in their business’s future. The press release announcing the findings also noted that more than 50% of these CEOs plan to adopt these technologies by the year 2019.
In terms of where AI will prove most impactful, respondents listed IT, sales, and information security as the top three priorities for the technology. The 6,000 CEOs surveyed also said they expect a 15% return on their AI investments.
The UK oil group is planning a fivefold increase in its data capacity over the next three years, and Ahmed Hashmi, head of technology for BP’s exploration and production business, claims the biggest efficiency gains are still to come.
More than 99 per cent of oil and gas wells operated by BP around the world are equipped with sensors that produce a constant flood of real-time data on production performance as well as the condition of infrastructure, Mr Hashmi said. This information is fed into a cloud-based storage system which allows BP engineers anywhere in the world to access the information. “The vision is to have absolute knowledge of what’s going on in the field,” Mr Hashmi told the Financial Times. “Increasingly, we can improve reliability and safety by predicting what is going to happen before something goes wrong.”
John Naughton, professor of the public understanding of technology at the Open University, says that as the legal chatbot DoNoPay shows, automation may only affect the repetitive parts of white-collar work.
DoNotPay (a chat bot which helps you fight parking tickets, tackle disputes with your landlord, etc.) provides a terrific illustration of how technology can be used for socially useful and democratic purposes. More important, though, it also suggests a better way of thinking about robotics and work – by making distinctions between tasks that can and should be automated, and those for which human experience, sensitivity, and creativity are necessary.
They discuss the applications of data science and AI in healthcare, what hospitals and healthcare systems are doing to adopt this kind of technology, and how this approach can be extended to other forms of enterprise. This interview was conducted in-person at BoostrapLabs annual AI conference in SF.