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Every Company is an AI Company: Now, Near Future, or Distant Future?”

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About this Bombay Management Association Webinar :
“Every company now is an AI company. The industrial companies are changing, the supply chain…every single sector, it’s not only tech.” said Steven Pagliuca, CEO of Bain Capital at the 2019 World Economic Forum. Prof Dr Sheth will provide us with an anecdotal review through a broad variety of applications of AI. He is hopeful that it will help managers start thinking of new business opportunities and new revenue/business models in the context of rapid penetration of AI technologies everywhere. through this webinar, he will put light on the questions like Is AI just hype or something already happening? If it has not happened in your industry, is it impending?
https://bma-india.com/event/every-company-is-an-ai-company-now-near-future-or-distant-future/

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Every Company is an AI Company: Now, Near Future, or Distant Future?”

  1. 1. Every Company is an AI Company: Now, Near Future, or Distant Future? Bombay Management Association Webinar: May 13 @ 5:00 pm - 6:00 pm IST Prof. Amit Sheth Founding Director, Artificial Intelligence Institute #AIISC University of South Carolina, Columbia, SC, USA http://aiisc.ai 1
  2. 2. (Big) Data - a key driver for AI Source: Raconteur, taken from http://rcnt.eu/un8bg
  3. 3. “ Information is cheap. Understanding is expensive. Karl Fast, Professor of UX Design, Kent State University AI is about converting data into knowledge, insights and actions.
  4. 4. “ ◆ Every company now is an AI company. The industrial companies are changing, the supply chain...every single sector, it’s not only tech. Steven Pagliuca (CEO of Bain Capital) @ WEF2019 5
  5. 5. 6
  6. 6. National Research Investment in AI 7 Increases in federal funding investments (DARPA $2B, NSF, etc)
  7. 7. “ ◆ While US is ahead in AI research, China is significantly ahead in AI development and monetization Kai-Fu Lee, CEO of Sinovation Ventures, Author of “AI Superpowers” Former President of Google-China 8
  8. 8. “ ◆ India will need to use technology to leapfrog, and there I think Artificial Intelligence will take the center stage. Amitabh Kant, CEO, NITI Aayog 9
  9. 9. India is late to the game (e.g., in setting a national policy, creating and education and research ecosystem), but …. Credit: economist.com
  10. 10. But in skills training, adoption and application, India can do reasonably well.
  11. 11. ReWire for Growth | Accenture 12 AI has the potential to add US$957 billion, or 15 percent of India’s current gross value in 2035. AI is expected to raise India's annual growth rate by 1.3 percentage points—in a scenario of intelligent machines and humans working together to solve the country's most difficult problems in 2035.
  12. 12. 13
  13. 13. Areas according to Mr. Kant: mobility: EV, LI batteries; mobile tech NW. But I feel wherever there is digitization: dHealth, fintech, education, auto mfg, pharma (mfg and delivery), agr (food proc), telemedicine… 14
  14. 14. Game Changing scenario - example of unusual shift Post pandemic, 80% of healthcare is telehealth/ dHealth. - Eric Schmidt, former Google CEO. Practically all mental health services for now are online. Medicare and insurance companies have suddenly expanded reimbursements that were not allowed in pre- pandemic times. Opportunity to leapfrog, similar to going mobile when India could not provision landlines to match the needs. Just as teleradiology has flourished in India, India can capture significant market in all areas of healthcare that are not subject to telehealth/dHealth.
  15. 15. Revolutionary role of AI - but not in isolation When we talk about AI, it is not just computing or algorithms, or deep learning (it is of course important)…. it is the ability to draw insights from broad variety of data and other digital tools: - Internet of Things/Sensors - Biotechnology - Behavioral Science/psychology - understanding of humans - Digital Payment Management needs to appreciate the need to put together multidisciplinary teams!
  16. 16. LEAD and ADAPT 17 Knowledge-infused Learning Explainable AI Chatbots & integration with Robots (with special emphasis on health/social good/education) Augmented Personalized Health, Medical Explainability (M,N) Surveillance Capitalism (Business & Law) Disinformation, Radicalization (I&C) Wellness, Nutrition, Policy (Health) AI/intelligent Grading (Education)
  17. 17. Illustrative examples for today’s talk ◆ Pharmacy ◆ Public Health ◆ Personalized Health ◆ Social Good ◆ Education ◆ Personalized Medicine/Clinical/ Nursing ◆ Social Work ◆ Law ◆ Journalism ◆ Financial …. 18
  18. 18. DRUG DISCOVERY SELECTION OF PATIENTS FOR CLINICAL TRIALS AUTOMATION OF PHARMACEUTICAL REPORTING ○ Modelling of different types of cancer cells to work out what conditions allowed the disease to develop ○ Use the information to try and create new treatments ○ AI Matches drugs to larger databases of patients quicker than human annotation ● Using data from clinical trials to generate sections of the CSR report ● Using AI to automate pharma reports - Pharmocovigilance ● Frees up medical writers’ time ● Allowing them focus on more high value analysis and adding technical insight to reports.Automate report writing Source: https://pixabay.com/de/illustrations/medizin-pharma-pille-flasche-2801025/, https://www.resources.yseop.com/CSR-use-case AI in Pharmaceuticals PHARMA
  19. 19. AI in Pharmaceuticals ADVERSE DRUG REACTIONS Drug Use/Abuse: Loperamide Discovery ▰ In a Web forum dataset, it was observed that users reported taking the anti-diarrhea treatment drug Loperamide (sold over the counter in Imodium) to self-medicate from withdrawal symptoms. The opioid addictions treatment drugs Buprenorphine and Methadone are commonly prescribed for treatment of withdrawal symptoms. Until now, it was unknown that Loperamide, can be (and is being) used for the same purpose. Which is more, it was observed that users reported the possibility of mild psychoactive (opiated) effects from megadosing - which is the practice of taking severely excessive amounts of a drug. ▰ Three toxicology studies followed citing our work. ▰ FDA Warning in 2016. ▰ More at: http://wiki.aiisc.ai/index.php/PREDOSE Source: R. Daniulaityte, R. Carlson, R. Falck, D. Cameron, S. Perera, L. Chen, A. P. Sheth. "I Just Wanted to Tell You That Loperamide WILL WORK": A Web-Based Study of Extra-Medical Use of Loperamide. Journal of Drug and Alcohol Dependence. 130(1-3): 241-244, 2013.
  20. 20. Knowledge Graph enhanced Natural Language Processing
  21. 21. Psychdemic: Measuring Spatio- Temporal Psychological Impact of Novel Coronavirus through Social Quality Index Insights from semantic analysis of Social Media Big Data
  22. 22. Public Health - COVID-19 Big Data (USA) How does real-world events and policy decisions (school closing, nonessential business closing, number of cases, availability of clinical services), varying by time, geography (e.g., state), and demography (GenZ, Millennials, ..) impact public and social health, such as ◆ Mental health including depression ◆ Addiction (alcohol, opioid, marijuana, etc) ◆ Domestic Violence COVID-related Big data: >800 Million tweets (~45M with location), ~700K news articles "A feeling of hopelessness. Seems I am in a dark age. #coronavirus #COVID19"
  23. 23. Results: Relative State Rankings Reveal Patterns e.g., IN, NH, OH, OR, WA, WY are worsening. SQI Ranking April 4 - 10 SQI Ranking March 14 - 20 SQI Ranking March 21 - 27 SQI Ranking March 23-April 3
  24. 24. Results: Cluster --A Non-Linear SQI Ranking 25 WI, RI, NV, NJ, CT, LA, OK. SQI worse SQI better SQI better SQI worse Frequency Depression: 91,480 Addiction: 103549 Anxiety: 88293 Total: 283322 Frequency Depression: 62825 Addiction: 81400 Anxiety: 54184 Total: 198409 Frequency Depression: 58223 Addiction: 76232 Anxiety: 41484 Total: 175949 Frequency Depression: 78061 Addiction: 87463 Anxiety: 63865 Total: 229389 March 14-20 March 21-27 March 28-April 3 April 4-10
  25. 25. Results: Influence of External Events 26 SQI worse Cluster 4: CT, LA, NJ, NV, OK, RI, WI. School Closures: CT, LA, NJ, NV, RI, WV, WI Business Closures: CT, LA, NJ, RI, WV, WI Social Distancing Reg: LA, NJ, RI, WV, WI Business Relief: WI Unemployment increase: CT 2.5K %, LA 2.5K %, NJ 1.2K %, NV 1.2K %, OK 1.2K %, RI 2.5K %, WI 1.2K %. Stay at home: CT, LA, NJ, OK, RI, WI, WV Extension School: CT, WV Major Disaster: NJ Business Relief: NJ Unemployment increase: CT 180%, LA 0 %, NJ 64 %, NV 0 %, OK 99 %, RI -23%, WI 99 %. Major Disaster: CT, WV Strict Social Dist: CT, RI Extensions deadlines: CT Medical shortage: NJ Extension Stay home: OK Extension School: RI Extension Business Closure: RI Business Relief: NJ, RI Individual Relief: RI Unemployment increase: CT 0%, LA 5 %, NJ 3 %, NV 11 %, OK 7 %, RI 0%, WI -5 %. Extension School: CT Extension Stay home: LA Strict Social Dist: NJ Business Relief: WI Cluster 5: FL, GA, MI, NE, TN, VA, WV. School Closures: FL, GA, MI, TN, VA, WV, Business Closures: WV, MI Social Distancing Reg: FL, MI, NE, TN, VA, WV, Business Relief: FL, GA, MI, NE, TN, VA Individual Relief: TN, VA Unemployment increase: FL 600%, GA 650%, MI 180%, NE 70%, TN 180%, VA 180%, WV 600% Stay at home: MI, WV Shelter in Place: GA Business Closure: GA, TN Extension School: GA, WV Major Disaster: FL Business Relief: TN Individual Relief: TN Unemployment increase: FL 3.1K%, GA 3K%, MI 1.8K%, NE 200%, TN 700%, VA 1.6K%, WV 1.7K% Stay at home: FL, VA Shelter in Place: TN Major Disaster: GA, MI, TN, VA, WV Strict Social Dist: GA Extension School: GA, MI Unemployment increase: FL -25%, GA 190%, MI 27%, NE 8%, TN 26%, VA 33%, WV 0% Extension School: GA Extension Stay home: MI SQI worse SQI worseSQI worse SQI better SQI better SQI better SQI better March 14-20 March 21-27 March 28-April 3
  26. 26. 27 Content of GenZ & Millennial Expressions
  27. 27. Patient-generated Health Data (PGHD) is becoming the most important data in healthcare. Source: https://patientengagementhit.com/news/what-are-the-pros-and-cons-of-patient-generated-health-data https://www.healthaffairs.org/doi/full/10.1377/hlthaff.2015.1362?siteid=healthaff&keytype=ref&ijkey=6C1y7.jaIT7q U&#aff-1 “Real world evidence can help answer questions that are relevant to broader patient populations or treatment settings where information may not be captured through traditional clinical trials” Personalized Digital Health
  28. 28. kHealth Asthma: A multisensory approach for personalised asthma care in children
  29. 29. 30 Patient Health State Medication Compliance Environmental Triggers Risk assessment model Semantic Perception Personal level Signals Public level Signals Domain Knowledge Population level Signals GREEN -- Well Controlled YELLOW – Not well controlled Red -- poor controlled Asthma Control Level Prediction
  30. 30. 31 NOURICH: Nutrition Management Chatbot ◆ Many diseases can be controlled by proper diet management - diabetes, obesity, hypertension and so on. ◆ Monitoring individual's diet and cumulative calorie intake and recommending meals can help them in making informed decisions about their meals. A personalized nutrition management chatbot incorporated with AI techniques can aid and assist the users in this process
  31. 31. If the video does not play, check out NOURICH video at: http://wiki.aiisc.ai/index.php/KHealth_Chatbots
  32. 32. 33 Techniques: ● Image Recognition: Semi-supervised learning and meta learning to utilize unlabelled data. ● Volume estimation: Image segmentation to identify food items and estimate volume. ● Nutritional Information: Using large nutrition knowledge base to estimate nutrition. ● Food recommendation: Personalized food recommendation using user-specific knowledge graph (if recommended by clinician) that stores user’s health condition, food preferences and so on. Applications ● Type-1 Diabetes: Patients need to know daily amount of carbohydrate intake. ● Hypertension: Patients need to avoid high sodium foods and follow healthy food habits. AI Techniques and Applications
  33. 33. 34
  34. 34. Source: https://www.cbinsights.com/research/ai-healthcare-startups-market-map-expert-research/
  35. 35. 36 DisasterRecord substantially reduces the burden of analysis, interpretation, and decision making during major disasters. It analyzes geographical data and integrates satellite imagery for better decision making. ● Humanitarian organization: analyze the situation at a community level for deploying and mobilizing necessary help. ● First response coordinator: monitor a specific type of emergency needs. ● Affected individuals: need to know about the nearest available help. ● Persons wishing to provide support: identify current needs in the geographic proximity for the type of help they can provide. Disaster Coordination
  36. 36. Also online at: http://wiki.aiisc.ai/index.php/DisasterRecord
  37. 37. “ Personalized Learning Platform for Everyone through world’s best Artificial Intelligence Platform in Education Improve outcome through Behaviour nudges, Machine Learning AI in Education with Embibe (India):
  38. 38. Multi-dimensional graph of concepts that captures the flow of learning through life. Educational Knowledge Base Intelligent content authoring and curation Educational data lake Intelligent intervention layer Machine learning and education domain knowledge combined to deliver robust learning outcomes for students and efficiency in operations for institutions Massive usage data lake created and leveraged to power intelligent intervention & content authoring Content creation & curation platform designed to serve content need while ensuring diagnosis and remedy happens at personalised level AI PLATFORM FOR EDUCATION STUDENT PRODUCTS TEACHER PRODUCTS PARENTS 4 Key Components STUDENT
  39. 39. AI-powered solution landscape
  40. 40. Impact on Education using AI 41 ● User Intelligence ○ Learning outcome oriented learning ○ Personalized learning paths ● Content Intelligence ○ Practically infinite content availability ■ Automated content creation, curation and tagging ● Mentor Intelligence ○ Automated optimal lesson plans ○ Social Emotional Learning (SEL)
  41. 41. Parting Thoughts 42 Indian needs to be globally competitive, esp. to capture unique market opportunity due to transformational events. It is unlikely that a company can be globally competitive without significant application of AI. Education and training from Indian university is not world-class. Just as IT companies provided training to new recruits, robust training program in AI will be needed in the short term, and even in medium term. Management will need to be “AI-literate”, engaged and well informed to define business opportunity, develop and quickly adapt business model, recruit talent, and execute smartly.
  42. 42. 43aiisc.ai #AIISC Artificial Intelligence Institute

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