Saturday Keynote at #ODSCWest Carrie Grimes Bostock - Data Science & Automated Decision Making. Automation has inputs, model(s) and potential outputs for action.

What is the goal of your models? Interpretability is important, but not the only thing. Other measures exist, but understanding your model is important to prevent outcomes, override recommendations, and to connect models to other systems - or stacks of models & systems. #ODSCWest

Example: placing racks in the Santa Clara data centre. Considerations, restrictions on space, power, future use of space, etc. Also: People install racks. They need to be able to intervene based on info that the placement model doesn't have. #ODSCWest

So, what do we want out of the system? Future planning, large scale, ability to move, change or adapt. And test. This is HARD to do in a non-interpretive model. #ODSCWest

Example: human-guided experiments in fusion at @GoogleAI ai.googleblog.com/2017/07/so-the…

Optometrist model: human-labelled interference. Repeat recent best shots, pick a new point, expert marks interest or risk at point. Then test and take steps in parameter space to keep moving forward - but cautiously. Now develop a model to help humans in the space. #ODSCWest

Importance of interpretability in these systems
- need to be able to test and integrate
- need to design solutions in context
- models will (and need to) change & evolve
- consider changes in the system.

#ODSCWest

In a nutshell: #Interpretability is super important if you're doing #DataScience at scale. Would also apply to policy, legislation, regulations. (And then all these systems actually interact in the real world.) #ODSCWest

Next up: Derek Haoyang Li - Developed AI tutor - @YixueSquirrelAi - on the future of AI:
- Know-all & remember all - ability to absorb and recall perfectly
- Debater: predict positions of opponent debaters and adjust position
(con't)

(.. cont)
- Understanding: focus on where students need knowledge

Trying to understand everything in every student's mind and design knowledge paths based on student knowledge & activity.

Analogy: a GPS for the mind. Map all the streets, know the buildings, know the traffic patterns.

Example: TouTiao [Tik Tok] - #AI News org. Applies tags to users instead of catagorizing them. Downloads surpassed FB, Twitter, Instagram in Sept 2018.

1M students already. Map knowledge points. How long does it take a student to absorb a knowledge point? Always different - so build this into the plan. Each student needs their own classroom. Models for #Student #Content #Teaching #Prediction #ODSCWest

#AI ability to evaluate massive potential futures in instants.

- Break knowledge points down into "pixels".
- Evaluate video capture, behaviour, time

AI Tutor learned from expert teachers for 3 years. It is now better.
& Scariest part of AI == self-evolving.

Previous example: SRI Motobot #ODSCWest

Today, we are still working on vertical or specific #AI - but glimpses of General AI are appearing (@Google uses Alpha Go to save electricity) #ODSCWest

Squirrel AI: also breaking down and decomposing the skills of learning - info filtering, pattern identifying, backward reason, creating general models, etc. Helps students to explore new knowledge points. #ODSCWest

Thought: Apply to VR environment? Reminds me of the Vulcan school in the Star Trek reboot. #ODSCWest

Prediction: #AI will take over mental labour in next 20 years. Crazy big ambitious thinking here. Definitely a space to watch. #ODSCWest

Next up: Daphne Koller - CEO and founder of Insitro @DaphneKoller
- Standford Academics
- Saw huge need for high quality online courses
- Founded Coursera in 2012
- Left Aug 2016 (Coursera in a good place)
- Now focusing on AI in human health with Insitro
#ODSCWest

Vision for Coursera: anyone anywhere can transform their lives through high-quality learning experiences. #ODSCWest

Advice for entrepreneurs: difference between success and failure can be sticking with it and showing grit. Also: don't become an entrepreneur because you want to be one - find the problem you are burning to solve. Good blog on subject here: #ODSCWest medium.com/@benwerd/found…

Today in #AI we have bilingual people
- get machine learning
- also have domain knowledge

Need both to see opportunities and see where problems lie. Insitro is bringing #MachineLearning as a core skill in field of drug development

#ODSCWest

Problem: cost of successful drugs need to cover cost of unsuccessful drugs. Looking to apply #AI to this and other problems. #data in this field is incredible. Now also have #CRISPR #ODSCWestt insitro.com

#CRISPR is amazing BTW. #ODSCWest en.wikipedia.org/wiki/CRISPR

Oooh. Question from moderator. Bilingualism is cool. What about ethical thinking?

A: #Ethics is super important. #AI applied without considering #bias and #ethics can do serious damage, even with no ill intent. #ODSCWest

Example: do a google image search for #CEO - how many women do you see? #ODSCWest google.com/search?q=CEO+i…

Also points to the need for interpretable models (which has been a big theme here this week). distill.pub/2018/building-… #ODSCWest