Solving the challenge of securing AI and machine learning systems | Microsoft on the Issues

Solving the challenge of securing AI and machine learning systems | Microsoft on the Issues

Today, in collaboration with Harvard University’s Berkman Klein Center, we at Microsoft are publishing a series of materials we believe will contribute to solving a major challenge to securing artificial intelligence and machine learning systems. In short, there is no common terminology today to discuss security threats to these systems and methods to mitigate them, and we hope these new materials will provide baseline language that will enable the research community to better collaborate.

Here is why this challenge is so important to address. Artificial intelligence (AI) is already having an enormous and positive impact on healthcare, the environment, and a host of other societal needs. As these systems become increasingly important to our lives, it’s critical that when they fail that we understand how and why, whether it’s inherent design of a system or the result of an adversary. There have been hundreds of research papers dedicated to this topic, but inconsistent vocabulary from paper to paper has limited the usefulness of important research to data scientists, security engineers, incident responders and policymakers.

The centerpiece of the materials we’re publishing today is called “Failure Modes in Machine Learning,” which lays out the terminology we developed jointly with the Berkman Klein Center. It includes vocabulary that can be used to describe intentional failure caused by an adversary attempting to alter results or steal an algorithm as well as vocabulary for unintentional failures like a system that produces results that might be unsafe

The entire post Solving the challenge of securing AI and machine learning systems appeared first on Microsoft on the Issues.

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PyDev of the Week | Joel Grus

PyDev of the Week | Joel Grus

This week we welcome Joel Grus (@joelgrus) as our PyDev of the Week! Joel is the author of Data Science From Scratch: First Principles with Python from O’Reilly. You can catch up with Joel on his website or on Github. Let’s take some time to get to know Joel better!

Can you tell us a little about yourself (hobbies, education, etc):

 

In school I studied math and economics. I started my career doing quantitative finance (options pricing, financial risk, and stuff like that). I got very, very good at Excel, and I learned a tiny amount of SQL. But I kind of hated working in finance (and also I got laid off), so I joined an online travel startup as a “data analyst” doing BI stuff (lots of spreadsheets, lots of SQL, some very light scripting). That startup got acquired by Microsoft, who at the time had basically no idea what to do with my more-than-a-financial-analyst-less-than-a-software-engineer skillset. (Nor did I, really.)

 

Then in 2011 I saw that the winds were blowing toward “data science”, so I sort of BS-ed my way into a data scientist job at a tiny startup. I took a bunch of Coursera courses to fill in gaps in my knowledge, and then I learned to write (ugly) production code and discovered I really enjoyed building software. Through doing well in coding competitions I had the opportunity to interview for a software engineer job at Google, so I spent 6 really hectic weeks cramming computer science and then somehow passed the interview. I spent a couple of years at Google, and then I found I missed doing data and ML stuff, and so now I’m at the Allen Institute for Artificial Intelligence, where I build deep learning tools for NLP researchers. My current job is right at the intersection of deep learning and Python library design, which is a pretty great match for my interests.

 

I don’t really have time for hobbies 😢. I have an 8-year-old daughter, and I spend a lot of my free time with her, and then I keep agreeing and/or volunteering to write things and give talks and make livecoding videos, which takes up most of the rest. And then I have a podcast and a Twitter to stay on top of. I have long-term hobby goals of (1) learning jazz piano and (2) writing a novel, but I’m not really making much progress on either.

 

Why did you start using Python?

 

A long, long time ago I was taking a “Probability Modeling” class that was taught using Matlab. The site license for Matlab was only valid on-campus, which meant I couldn’t work on the assignments at my apartment, which was where I preferred to work. I discovered that there was a Python library called Numeric (the predecessor of NumPy) that would allow me to do the numerical-simulation things I needed to do, so I learned just enough Python to be able to do my assignments. Several years after that I had a job, and I inherited a bunch of Perl scripts, and I really didn’t want to maintain Perl code, so I started migrating them to Python, and the rest is history.

 

What other programming languages do you know and which is your favorite?

 

About 10-15% of my job involves writing JavaScript / React, which I actually really enjoy. (I might enjoy it less if it were 100% of my job.) The first year I was at AI2 I worked mostly in Scala, and after that I briefly worked on a project that was in Go. At Google I wrote primarily C++. The startup I was at before that used F#. For fun I used to write Haskell and PureScript. Part of me still dreams of having a Haskell / PureScript job, but at this point I’m so comfortable working in Python (and Python has so deeply entrenched itself as the language for doing machine learning) that it seems unlikely I’ll ever make the switch.

 

Thanks for doing the interview!

from The Mouse Vs. The Python http://bit.ly/2LlQmZn

Amazon Rekognition Achieves HIPAA Eligibility | Amazon Web Services

This is quite the breakthrough. Now some advanced services can be developed that will satisfy HIPAA requirements, which will allow better patient outcomes and secure effective data.

 

Amazon Rekognition is a deep learning-based computer vision service that makes it easy to add image and video analysis to your applications…See more here.

Are self-driving cars the future of mobility for disabled people?

file-20170918-24089-1jhnwatCATS Ride Transit, are you listening. Since you are subject to paratransit rising costs like all other agencies of its type, here is an opportunity to become a leader, not a follower, in this necessary research and study. Will have far more impact on the community than chasing the waterfall that is Amazon HQ 2.

Are self-driving cars the future of mobility for disabled people?