Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead Rudin et al., arXiv 2019 It's pretty clear from the title alone what Cynthia Rudin would like us to do! The paper is a mix of technical and philosophical arguments and comes with two main takeaways for me: firstly, a sharpening of my understanding of the difference between explainability and interpretability, and why the former may be problematic; and secondly some great pointers to techniques for creating truly interpretable models. A model can be a black box for one of two reasons: (a) the function that the model computes is far too complicated for any human to comprehend, or (b) the model may in actual fact be simple, but its details are proprietary and not available for inspection. In explainable ML we make predictions using a complicated black box model (e.g., a DNN), and use a second (posthoc) model created to explain what the first model is doing. A classic example here is LIME, which explores a local area of a complex model to uncover decision boundaries.

A few years ago this month, Portland, Oregon artist Darius Kazemi watched a flood of tweets from would-be novelists. November is National Novel Writing Month, a time when people hunker down to churn out 50,000 words in a span of weeks. To Kazemi, a computational artist whose preferred medium is the Twitter bot, the idea sounded mildly tortuous. "I was thinking I would never do that," he says. "But if a computer could do it for me, I'd give it a shot."

Barcelona-based startup Prometeo has developed an AI-based cognitive health monitoring platform in hope that one day it will be used to monitor the health of firefighters while they are out battling brutal wildfires. Co-founder Salome Valero explained the development of the platform came about following concerns that were raised by one of their own team members who is a veteran firefighter. "When the firefighters are fighting against fire, they are breathing in a lot of toxins which can be dangerous for their health … and some of the immediate effects they feel from breathing in smoke is getting headaches. But there is evidence they can suffer respiratory diseases, cancer, and stress disorders," she told ZDNet, during IBM Cloud Innovation Exchange in Sydney last week. "The problem is there currently isn't a lot of data about firefighters' vitals, but because we have this real-time capability, we are will be able to monitor them." Working primarily with firefighters from Catalonia, Prometeo, which was recently announced as the winner of IBM's Call for Code 2019 competition, has developed a smartphone-sized device that straps on a firefighter's arm.

It's time for employers to start preparing for legislation recently signed into law in Illinois, the Artificial Intelligence Video Interview Act. The new law, which takes effect on January 1, 2020, regulates Illinois employers' use of artificial intelligence (AI) in the interview and hiring process. Under the AI Video Interview Act, employers that record video interviews and use AI technology to analyze applicants' suitability for employment must: Employers that conduct such interviews may not distribute videos to other parties, except as necessary to obtain expert assistance in evaluating a candidate's fitness for a particular position. In addition, an employer has only 30 days to destroy all video copies of the interview if an applicant seeks such destruction. This law highlights a myriad of privacy concerns for employers evaluating the costs and benefits of incorporating AI technology into their hiring practices.

Why did you think to combine Qiskit, a quantum-computing framework, with PyTorch, a machine-learning framework? Karel Dumon: Classical machine learning is currently benefiting hugely from the open-source community, and this is something we want to leverage in quantum too. Our project focuses on the potential application of quantum computing for machine learning, but also on the use of machine learning to help progress quantum computing itself. Through our project, we hope to make it easier for machine learning developers to explore the quantum world. Patrick Huembeli: To that effect, it makes Qiskit very accessible for people with a classical machine learning background -- they can treat the quantum nodes just as another layer of their machine learning algorithm.

And, once again, they're doing it by teaching a computer to find previously unseen changes in patterns in CT scans taken when the lung cancer is first diagnosed compared to scans taken after the first 2-3 cycles of immunotherapy treatment. And, as with previous work, those changes have been discovered both inside -- and outside -- the tumor, a signature of the lab's recent research. "This is no flash in the pan -- this research really seems to be reflecting something about the very biology of the disease, about which is the more aggressive phenotype, and that's information oncologists do not currently have," said Anant Madabhushi, whose Center for Computational Imaging and Personalized Diagnostics (CCIPD) has become a global leader in the detection, diagnosis and characterization of various cancers and other diseases by meshing medical imaging, machine learning and AI. Currently, only about 20% of all cancer patients will actually benefit from immunotherapy, a treatment that differs from chemotherapy in that it uses drugs to help your immune system fight cancer, while chemotherapy uses drugs to directly kill cancer cells, according to the National Cancer Institute. Madabhushi said the recent work by his lab would help oncologists know which patients would actually benefit from the therapy, and who would not.

Frisco Public Library is named the Top Innovator in Customer Experience in the nation for the Library's artificial intelligence project. The annual award by the Urban Libraries Council recognizes innovative programs and practices from libraries across North America. "We celebrate Frisco Public Library for presenting a groundbreaking initiative that is sure to transform the community and inspire libraries across North America," said Urban Libraries Council President and CEO Susan Benton. The Urban Libraries Council is an innovation and impact tank of North America's leading public library systems. The winning project combines A.I. kits, coding, and classes making artificial intelligence accessible to entrepreneurs, students, and anyone looking to increase their skill set.

OK, let's start from the beginning: I just read that in 2018 the US government announced a new security clearance program - including for individuals in civilian roles - which would run "continuous evaluations" of all applicants, thanks to machine learning technology. The article itself highlights the obvious risks of such a system "going off the rails", but the really interesting questions here are: At least in certain cases, we may never know the answer to the first question because, as the article says, certain systems "offer little to no insight as to how their highly accurate predictions are actually made". But hey, we are only talking of national security, no big deal right? So let's focus on the second question. The article does correctly acknowledge my first thought when I read its title: "if the system works, it might actually generate deeper problems still".

I want to start off with a quick question – can you recognize the two personalities in the below image? I'm certain you got one right. For most of us early age math enthusiasts, the movie "A Beautiful Mind" is inextricably embedded into our memory. Russell Crowe plays the role of John Nash in the movie, a Nobel prize winner for economics (and the person on the left-hand side above). Now, you would remember the iconic scene often regarded as: "Don't go after the blonde". "….the best outcome would come when everyone in the group is doing what's best for himself and the group."

We have already established the fact that AI will certainly play a key role in transforming the future of Indian financial services. With various fintech business models in place, BFSI industry is now adopting the AI-based fintech solutions at a much larger scale than ever. "Most corporates, and increasingly governments as well, are experimenting with how to use AI to improve their processes and outcomes. The fintech industry is no exception and is, in fact, one of the leaders in its adoption," said Gaurav Jalan, Founder and CEO, mPokket. And this is not just one opinion.