Social Impact at Scale, One Project at a Time with Dr. Anjali Sastry (S1:E4)
Skills:
Staying Current in AI60%
MIT Chalk Radio, Season 1
Instructor: Anjali Sastry, Sarah Hansen
Subscribe here → https://chalk-radio.simplecast.com/
YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63YwKIMA9K08FFvdeBEl6Lo
*Description*
In this episode, Dr. Anjali Sastry describes how she redesigned a traditional independent study to encourage MBA fellows to find social impact solutions that scale.
*Episode Notes*
This episode explores a new kind of independent study. MIT has traditionally encouraged its Sloan MBA fellows to engage in international projects with partners around the globe. Our guest, Dr. Anjali Sastry, has led over 100 groups of MBA fellows in these projects. But she recently changed the structure of the class so that instead of signing on to projects developed by instructors, students are now able to develop their own projects based on their own interests. All the new projects in this course called 15.960 New Executive Thinking Social-Impact Projects involve applying technology in new ways to find solutions to common problems worldwide. In one project, for example, a student employed data analytics to improve financing prospects for small-scale farmers in Brazil and elsewhere. Sastry finds that mentoring a variety of students with disparate interests presents a real challenge, because it often involves working in areas beyond her own area of expertise. And keeping track of the various projects required her to develop a very structured process for students to use in reporting their progress. It’s worth the extra effort, though it isn’t easy, says Sastry. “Teaching this way is incredibly rewarding, and also really scary.”
Relevant Resources:
MIT OpenCourseWare
https://ocw.mit.edu/index.htm
The OCW Educator Portal
https://ocw.mit.edu/educator/
Dr. Sastry’s Social-Impact course on OCW
https://ocw.mit.edu/courses/sloan-school-of-management/15-960-new-executive-thinking-social-impact-technology-projects-fall-2017-spring-2018/
Other courses by Dr. Sastry on OC
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Playlist
Uploads from MIT OpenCourseWare · MIT OpenCourseWare · 11 of 60
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21. Post Trade Clearing, Settlement & Processing
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10. Financial System Challenges & Opportunities
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7. Technical Challenges
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3. Blockchain Basics & Cryptography
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19. Primary Markets, ICOs & Venture Capital, Part 1
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1. Introduction for 15.S12 Blockchain and Money, Fall 2018
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Chalk Radio, A Podcast about Inspired Teaching at MIT (Teaser)
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Nuclear Gets Personal with Prof. Michael Short (S1:E1)
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How Africa Has Been Made to Mean with Prof. Amah Edoh (S1:E2)
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Making Deep Learning Human with Prof. Gilbert Strang (S1:E3)
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Social Impact at Scale, One Project at a Time with Dr. Anjali Sastry (S1:E4)
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Film is for Everyone with Prof. David Thorburn (S1:E5)
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Lecture 12: Aircraft Performance
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Lecture 3: Learning to Fly
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Lecture 13: Interpreting Weather Data
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Lecture 21: Weather Minimums and Final Tips
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Hand-on, Minds On with Dr. Christopher Terman (S1:E6)
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Part 4: Eigenvalues and Eigenvectors
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Part 5: Singular Values and Singular Vectors
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Part 3: Orthogonal Vectors
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Part 2: The Big Picture of Linear Algebra
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Part 1: The Column Space of a Matrix
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Intro: A New Way to Start Linear Algebra
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9. Chromatin Remodeling and Splicing
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28. Visualizing Life - Fluorescent Proteins
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20. Roth's theorem III: polynomial method and arithmetic regularity
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8. Szemerédi's graph regularity lemma III: further applications
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19. Roth's theorem II: Fourier analytic proof in the integers
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12. Pseudorandom graphs II: second eigenvalue
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1. A bridge between graph theory and additive combinatorics
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Special Episode: Teaching Remotely During Covid-19 with Prof. Justin Reich
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Spring 2020 Update from Dean Rajagopal
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S1E7: Unpacking Misconceptions about Language & Identities with Prof. Michel DeGraff
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Climate 101 Live
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Welcome for Volunteers (for EarthDNA's Climate 101)
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Learning to Fly with Drs. Philip Greenspun & Tina Srivastava (S1:E8)
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Thinking Like an Economist with Prof. Jonathan Gruber (S1:E9)
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2. Cyber Network Data Processing; AI Data Architecture
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1. Artificial Intelligence and Machine Learning
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2: Resistor Capacitor Circuit and Nernst Potential - Intro to Neural Computation
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14: Rate Models and Perceptrons - Intro to Neural Computation
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4: Hodgkin-Huxley Model Part 1 - Intro to Neural Computation
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18: Recurrent Networks - Intro to Neural Computation
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3: Resistor Capacitor Neuron Model - Intro to Neural Computation
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15: Matrix Operations - Intro to Neural Computation
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13: Spectral Analysis Part 3 - Intro to Neural Computation
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16: Basis Sets - Intro to Neural Computation
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20: Hopfield Networks - Intro to Neural Computation
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8: Spike Trains - Intro to Neural Computation
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7: Synapses - Intro to Neural Computation
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19: Neural Integrators - Intro to Neural Computation
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5: Hodgkin-Huxley Model Part 2 - Intro to Neural Computation
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6: Dendrites - Intro to Neural Computation
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17: Principal Components Analysis_ - Intro to Neural Computation
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12: Spectral Analysis Part 2 - Intro to Neural Computation
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11: Spectral Analysis Part 1 - Intro to Neural Computation
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9: Receptive Fields - Intro to Neural Computation
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10: Time Series - Intro to Neural Computation
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1: Course Overview and Ionic Currents - Intro to Neural Computation
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The Power of OER with Profs. Mary Rowe and Elizabeth Siler (S1:E10)
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