A team of researchers led by CSIRO's Data61, the data and digital specialist arm of Australia's national science agency, have developed a novel technique that could assist psychiatrists and other clinicians to diagnose and characterize complex mental health disorders, potentially enabling more effective treatments. Announced today at D61 LIVE in Sydney, the researchers revealed that using a simple computer game and artificial intelligence techniques, they were able to identify behavioral patterns in subjects with depression and bipolar disorder, down to subtle individual differences in each group. The study included 101 participants: 34 with depression, 33 with bipolar disorder, and a control group of 34 subjects. The computer game presents individuals with two choices, and tracks their behavior as they respond. The complex data collected from the game is analyzed through artificial neural networks--brain-inspired systems intended to replicate the way that humans learn--which are able to disentangle the nuanced behavioral differences between healthy individuals, and those with depression or bipolar disorder.

Q: Tell us about your work on trusted microelectronics. David Crandall: Our role in this project is to use computer vision and machine learning techniques to help ensure the integrity of the supply chain around microelectronics. One way is to use computer vision to inspect integrated circuits to see whether there is something suspicious that might suggest they are damaged or counterfeit. The goal of computer vision is for computers to be able to understand the visual world the way people do. Computers have been able to take and store pictures for decades, but they haven't been able to know what is in a photo -- what objects and people are in it, what is going on, and what is about to happen.

Research and development for new drugs is both an expensive and lengthy process, often lasting years, if not decades. With the development of artificial intelligence technology however, this process is both becoming more cost-efficient and shorter, something that is expected to exponentially accelerate the development of new drugs. According to Brendan Frey, founder and CEO of AI-based drug discovery company, Deep Genomics, developing drugs has traditionally been like gambling, "It's like the Big Pharma companies come into a casino, put a million-dollar coin into a slot machine and with some probability like 10% or something, they get a win (Robertson: 2019)." This is where AI comes in. Until now, Deep Genomics has developed over 20 machine learning systems trained from both public and proprietary data to screen for disease-causing mutations while looking for drug targets.

In this episode, I am with Dr. Charles Martin from Calculation Consulting a machine learning and data science consulting company based in San Francisco. We speak about the nuts and bolts of deep neural networks and some impressive findings about the way they work.

Goodhart's Law states that "When a measure becomes a target, it ceases to be a good measure." At their heart, what most current AI approaches do is to optimize metrics. The practice of optimizing metrics is not new nor unique to AI, yet AI can be particularly efficient (even too efficient!) This is important to understand, because any risks of optimizing metrics are heightened by AI. While metrics can be useful in their proper place, there are harms when they are unthinkingly applied.

New funding has been announced to help businesses in the Scottish Highlands and islands benefit from digital technology. Highlands and Islands Enterprise (HIE) – a regional development agency of the Scottish Government – has launched a new £465,000 support programme for businesses in the Highlands and islands looking to develop their use of digital technology and innovation. It will provide specialist advice and events on topics such as data innovation, artificial intelligence, sensors and internet of things, as well as robotics and cyber resilience, with more than 2,500 businesses across the region are expected to benefit from the programme over the next three years. As well as businesses, the programme will also be accessible to established community groups and social enterprises. The programme was launched at a digital collaboration event at An Lochran in Inverness, attended by organisations including The Data Lab, Centre for Sensors and Imaging Systems (CENSIS), Scottish Business Resilience Centre (SBRC), DigitalBoost, ScotlandIS, EIT Digital, IoT Scotland and Interface.

Developers of new technologies, scaremongers, pessimists and people with something to sell are always predicting the demise of the recruitment industry and the end for recruitment consultants. We're all going to be replaced by robots. Some would say that the recruitment industry has been at death's door for at least twenty years. Reality indicates that people are rarely in a job for life, and job moves mean active candidates in the job market. Particularly in management consulting, good candidates are constantly seeking new challenges.

Artificial intelligence (AI) was once mainly brought up in science-fiction novels and movies rather than being something people encountered in their daily lives. However, it's now both advanced enough and accessible enough that individuals from almost all industries can make it suit their needs. In health care, AI is responsible for some particularly impressive trends. The technology opened new possibilities for how doctors treat and diagnose illnesses, resulting in a higher quality of care for the patients that need it. AI assists in both emergencies and ongoing care improvements.

Photo by Andras Vas on unsplash Previous posts in this series have highlighted the importance of human intelligence and emotion in education. We have traversed several emerging ideas, including the use of virtual teaching assistants (chatbots), ultra-personalised learning and machine intelligence, but the most important component in education is still the human element. Other jobs in society may already have been supplanted by robotics and artificial intelligence. Mostly, they are repetitive, low level or dangerous jobs, but replacing teachers with computers is neither desirable nor expedient. However, replacing some aspects of what teachers do is both effective and inevitable.

Roundup Welcome to this week's machine learning musings. Google has upset city officials by trying to improve its facial recognition technology, and the new TensorFlow 2.0 has been released. Google offered $5 gift vouchers to black homeless people and Atlanta city isn't happy: Facial recognition datasets are unfairly dominated with images of white men, so Google hired third-party contractors to go around recording people's faces by offering them vouchers. The temp agency, Randstad, were told to target people of darker skin, and, unfortunately, some of those people were homeless people living on the streets in Atlanta. The methods used to tempt them were ethically dubious.