An AI model showed Flint how to find lead pipes. What do you think they did after that?

❝ …Volunteer computer scientists, with some funding from Google, designed a machine-learning model to help predict which homes were likely to have lead pipes. The artificial intelligence was supposed to help the City dig only where pipes were likely to need replacement. Through 2017, the plan was working. Workers inspected 8,833 homes, and of those, 6,228 homes had their pipes replaced — a 70 percent rate of accuracy.

Heading into 2018, the City signed a big, national engineering firm, AECOM, to a $5 million contract to “accelerate” the program, holding a buoyant community meeting to herald the arrival of the cavalry in Flint…

❝ As more and more people had their pipes evaluated in 2018, fewer and fewer inspections were finding lead pipes…The new contractor hasn’t been efficiently locating those pipes: As of mid-December 2018, 10,531 properties had been explored and only 1,567 of those digs found lead pipes to replace. That’s a lead-pipe hit rate of just 15 percent, far below the 2017 mark…

❝ There are reasons for the slowdown. AECOM discarded the machine-learning model’s predictions, which had guided excavations. And facing political pressure from some residents, Mayor Weaver demanded that the firm dig across the city’s wards and in every house on selected blocks, rather than picking out the homes likely to have lead because of age, property type, or other characteristics that could be correlated with the pipes.

After a multimillion-dollar investment in project management, thousands of people in Flint still have homes with lead pipes, when the previous program would likely have already found and replaced them.

Life in America seems about as predictable as ever. Doesn’t have to be. Still, don’t get smug about analyzing the causes. Just fix it!

Autonomous robots can be bigots. Short-term payoffs work on machines, too.

❝ Showing prejudice towards others does not require a high level of cognitive ability and could easily be exhibited by artificially intelligent machines, new research has suggested.

Computer science and psychology experts from Cardiff University and MIT have shown that groups of autonomous machines could demonstrate prejudice by simply identifying, copying and learning this behaviour from one another…

❝ Though some types of computer algorithms have already exhibited prejudice, such as racism and sexism, based on learning from public records and other data generated by humans, this new work demonstrates the possibility of AI evolving prejudicial groups on their own…

❝ The findings involve individuals updating their prejudice levels by preferentially copying those that gain a higher short term payoff, meaning that these decisions do not necessarily require advanced cognitive abilities.

Your new self-driving car might not take you to the polls if it thinks you won’t vote for Trump or one of his lackeys.

Human Bankers Are Losing to Robots

❝ Something interesting happened in Swedish finance last quarter. The only big bank that managed to cut costs also happens to be behind one of the industry’s boldest plans to replace humans with automation.

❝ Nordea Bank AB, whose Chief Executive Officer Casper von Koskull says his industry might only have half its current human workforce a decade from now, is cutting 6,000 of those jobs. Von Koskull says the adjustment is the only way to stay competitive in the future, with automation and robots taking over from people in everything from asset management to answering calls from retail clients.

I imagine that Sweden’s labor culture will require, enable, a fair amount of retraining and education as required to meet this critical change in professional employment. Do I think anything comparable will be the response in the United States when similar job cuts take place?

That’s a rhetorical question, right?

Staying in touch with Atlas

Atlas is the latest in a line of advanced humanoid robots we are developing. Atlas’ control system coordinates motions of the arms, torso and legs to achieve whole-body mobile manipulation, greatly expanding its reach and workspace. Atlas’ ability to balance while performing tasks allows it to work in a large volume while occupying only a small footprint.

The Atlas hardware takes advantage of 3D printing to save weight and space, resulting in a remarkable compact robot with high strength-to-weight ratio and a dramatically large workspace. Stereo vision, range sensing and other sensors give Atlas the ability to manipulate objects in its environment and to travel on rough terrain. Atlas keeps its balance when jostled or pushed and can get up if it tips over.

Boston Dynamics rocks. I almost went to work for a precursor, a firm that ended up merged or “blended” into Boston Dynamics – before I left Boston in 1986. The chance to come to the Southwest and the Rockies was too tempting to walk away from. Surely might have been an interesting road to follow if I’d stayed.

AI System learned to master Rubik’s Cube in 44 hours

Meet DeepCube, an artificially intelligent system that’s as good at playing the Rubik’s Cube as the best human master solvers. Incredibly, the system learned to dominate the classic 3D puzzle in just 44 hours and without any human intervention.

“A generally intelligent agent must be able to teach itself how to solve problems in complex domains with minimal human supervision,” write the authors of the new paper, published online at the arXiv preprint server. Indeed, if we’re ever going to achieve a general, human-like machine intelligence, we’ll have to develop systems that can learn and then apply those learnings to real-world applications…

On the surface, the Rubik’s Cube may seem simple, but it offers a staggering number of possibilities. A 3x3x3 cube features a total “state space” of 43,252,003,274,489,856,000 combinations (that’s 43 quintillion), but only one state space matters — that magic moment when all six sides of the cube are the same color. Many different strategies, or algorithms, exist for solving the cube. It took its inventor, Erno Rubik, an entire month to devise the first of these algorithms…

RTFA. Interesting stuff – and you may as well get used to the topic whether you’re ready or not. Your next job interview might be with an entity built on systems like this. 🙂

AI diagnosis to make medical decisions is just about here


AP Photo/M. Spencer Green

❝ The US Food and Drug Administration approved this week the first software powered by artificial intelligence that replaces the need for a specialized doctor to interpret medical imagery.

The software is called IDx-DR, made by diagnostic AI startup IDx, and specifically analyzes images of the retina to detect whether a person with diabetes has a complication from the disease called diabetic retinopathy…

❝ Diabetic retinopathy is a complication of diabetes where blood sugar damages the back of the eye, according to the FDA, and is the main cause of the loss of vision for those with diabetes…

By allowing this software to be marketed in the US, the FDA is setting a bar for the accuracy needed in order for AI to take over for human doctors. When validating that the AI system worked, the FDA used images from 900 US patients. The software correctly detected more than mild diabetic retinopathy 87.4% of the time, and identified when patients did not have more than mild retinopathy 89.5% of the time. Accuracy for humans naturally varies from doctor to doctor, but for the FDA to approve the technology it “must provide for more effective treatment or diagnosis of a life-threatening or irreversibly debilitating disease or condition.”

No doubt a predictable percentage of Americans will demonstrate fear of this technology to a greater degree than any other educated nation. Part of that education and, more important, political processes, electoral politics, religious folderol, come together to work harder than anywhere else – to keep citizens from modernizing their lives and thinking. Why – we might even question authority.

Know any politicians who’ve noticed China becoming a global innovator?

❝ China has achieved much since 1978, when Deng Xiaoping initiated the transition to a market economy. In terms of headline economic progress, the pace of China’s transformation over the past 40 years is unprecedented. The country’s GDP grew by nearly 10 percent per year on average, while reshaping global trade patterns and becoming the second-largest economy in the world. This success lifted 800 million people out of poverty, and the mortality rate of children under five years old was halved between 2006 and 2015.

The question now is whether China, well positioned to become the world’s innovation leader, will realize that opportunity in 2018 — or soon after

❝ Earlier this month, Apple CEO Tim Cook declared that, “China stopped being a low-labor-cost country many years ago, and that is not the reason to come to China.” The country’s manufacturing strengths now lie in its advanced production know-how and strong supply-chain networks. Understandably, China’s leadership wants to increase productivity and continue to move further up the value chain.

I suggest you read the article. Even though your representatives in Congress will (1) probably act surprised by this and (2) stamp their little feet in anger and fear – fact remains that international trade usually is a cooperative affair and the political maundering is only for that telenovela called electoral politics.

Robot Fear Index stands at 30.9

❝ …Consumer adoption of artificial intelligence and robotics is already quite broad, and yet, fear of robots is also pervasive. We fear that they’ll replace our jobs or somehow overthrow us; and to be blunt, those fears are valid. That said, our 2017 survey indicates acceptance for these technologies continues to grow. Our most recent Robot Fear Index value of 30.9 (vs. 31.5 in late 2016) suggests that public perception of robots is essentially unchanged over the last year despite increased awareness of artificial intelligence, robotics, and the potential impact of these technologies. Notably, the related increase in media coverage of these issue does not seem be causing the rise in fear that we might expect. In fact, the slight year-over-year decline in our index value suggests slightly less fear of automation technologies.

❝ We believe that consumer awareness of robotics is closely correlated to the rise of domestic robots within households. Domestic robots are classified as robot vacuum cleaners, mops and lawn mowers, and over the next 10 years we believe this category will be one of the fastest growing robot markets in the world.

Glance through the whole report. Designed as a quarterly evaluation for investors – that, in itself, speaks volumes about the acceptability of robots and artificial intelligence growing in our society.

Personally, I think Gene Munster leads one of the sharpest firms dealing with advanced technology of any American investment firm.