Four short links: 13 June 2017
Drone Energy, Open Speech Data, Predicting Suicide, and Designing Amidst Algorithms
- Drone Energy Sources — what to look for, what the choices are, who’s doing interesting work.
- Can You Help Me Gather Open Speech Data? (Peter Warden) — I’ve put together a website that asks you to speak about 100 words into the microphone, records the results, and then lets you submit the clips. I’m then hoping to release an open source data set out of these contributions, along with a TensorFlow example of a simple spoken word recognizer.
- Predicting Suicide Accurately — the paper (use sci-hub for access) is interesting. This set of more than 5,000 cases was used to train the machine to identify those at risk of attempted suicide compared to those who committed self-harm but showed no evidence of suicidal intent. The researchers also built algorithms to predict attempted suicide among a group of 12,695 randomly selected patients with no documented history of suicide attempts. It proved even more accurate at making suicide risk predictions within this large general population of patients admitted to the hospital. Now the question becomes: how do we use this so as to minimize damage with false positives and false negatives, as well as true positives and negatives.
- Design in the Era of the Algorithm (Josh Clark) — The design and presentation of data is just as important as the underlying algorithm. Algorithmic interfaces are a huge part of our future, and getting their design right is critical—and very, very hard to do. My work has begun to turn to the responsible and humane presentation of data-driven interfaces. And I suspect that yours will, too, in very short order. While constructing these machine learning models is indeed heavy-duty data science, using them is not. Tons of these machine learning models are available to all of us here to build upon right now.
