The Future of Machine Learning in Production?
(closing remarks)
Christian Kaestner
Are Software Engineers Disappearing?
see also Andrej Karpathy. Software 2.0. Blog, 2017
Are Data Scientists Disappearing?
Ryohei Fujimaki. AutoML 2.0: Is The Data Scientist Obsolete? Forbes, 2020
Are Data Scientists Disappearing?
However, AutoML does not spell the end of data scientists, as it doesn’t “AutoSelect” a business problem to solve, it doesn’t AutoSelect indicative data, it doesn’t AutoAlign stakeholders, it doesn’t provide AutoEthics in the face of potential bias, it doesn’t provide AutoIntegration with the rest of your product, and it doesn’t provide AutoMarketing after the fact. -- Frederik Bussler
Frederik Bussler. Will AutoML Be the End of Data Scientists?, Blog 2020
SE4AI Research: More SE Power to Data Scientists?
SE4AI Research: More DS Power to Software Engineers?
Analogy
Analogy
(better tools don't replace the knowledge to use them)
My View
This is an education problem, more than a research problem.
Interdisciplinary teams, mutual awareness and understanding
Software engineers and data scientists will each play an essential role
DevOps as a Role Model
Joint responsibilities, joint processes, joint tools, joint vocabulary
One Last Time: Transcription
Feedback
Some things we tried
- Clear specifications for homework, pass/fail grading
- Open-ended reading quizzes
- Individual assignments and readings in pairs
- Credit for social activities
Feedback
- What was useful?
- What could be improved?
- Where did we overdo it with the homework?
- Ideas for better remote teaching?
Thank you!
