Stories of AI Failure and How to Avoid Similar AI Fails AND SUCCEED AGAIN

Starting a new AI project in 2019? Don’t fail prey to the hype. The new year will see a separation of the wheat from the chaff, and an AI fail at this stage could spell disaster for your project, team, and company. The author and speaker in this paper will discuss following failures

Fail: Microsoft’s AI Chatbot Corrupted by Twitter Trolls, Apple’s Face ID Defeated by a 3D Mask

Facebook had to shut down their “Bob” and “Alice” chatbots after the computers started talking to each other in their own language.

Artificial intelligence technologies cannot be built in isolation from the social circumstances that make them necessary,

This is a fantastic point. In the rush to stay ahead of the technology curve, companies often fail to consider the impact of their inherent biases. This is particularly dangerous for companies working in data analytics for healthcare, biotechnology, financial services and law.

Just look at Watson for Oncology: data bias and lack of social context doomed that AI project to failure and sent $65 million down the drain.

How to Get Real Value from Artificial Intelligence in 2019 Focus on solving a real business problem.

With the right business case and the right data, AI can deliver powerful time and cost savings, as well as valuable insights you can use to improve your business.

Dr. Shankar Ramamoorthy is currently working as Chief Customer Success Officer at Harman Connected Services , helping the Software Enabled Business of Harman. He was earlier Quality Business Partner –at Amdocs. - where he evangelized and implemented 40 patented Test Management Framework machine using BI/Analytics.

Dr Shankar is a TQM ( Total Quality Management) professional, who has spent much of his 26-years career managing change and improving software Quality Engineering efficiency through Data and Metrics driven Quality Management Systems.

He believes in evangelizing , coaching and mentoring test teams through inspirational leadership.

Shankar has a vast experience in setting up Test COE( Centre of Excellence),and has successfully carried out 6 rollouts on TPI/TMMI/Test Maturity frameworks for several companies.

He has handled the entire gamut of testing landscape right from Pre- Sales, Sales, Delivery and instituted a process temper in his earlier assignments.

I am passionate about how technology can transform business and I help conceive, plan and execute outcome focused technology initiatives. Specialties: Program Management, consulting, digital transformation

Rahul Lodhe is the Director for Analytics and IoT Leonardo Industry Innovation kit program. In his current role, he is responsible for conceptualizing and technical delivery of Leonardo accelerators working across IoT, Machine Learning, Analytics cloud and S4 applications. In past in was also responsible for development of TCO application for BOE and heading the Global Test center for the BI hybrid organization.

He has 14 years of experience in SAP and has worked across various departments in SLI and in multiple roles. His area of expertise  is the SAP business objects portfolio, SAP ERP  and SRM (procurement)  areas.  Before joining SAP he has worked extensively in the Database Administration area. He has over 18 years of software industry experience in various companies like TCS, Indiamarkets and now SAP.

Rahul is passionate about driving innovation in products and quality. Having couple of patents on improvement product quality applications.

Vishesh is having more than 17 years of industry experience in institutionalising and delivering technical solution in analytics, bigdata, Robotics and conversational artificial intelligence.

Currently working in Concentrix as GM - Global Strategic Assets Area– Intelligent Process Automation and Conversational AI. Prior to that had worked in HP-Analytics, GENPECT, Bharti and ISOFT delivering solutions for Intelligent Process Automation, Analytics, Shared Services, Insurance/Reinsurance, Risk Assessment and Data Modelling, Telecom and Manufacturing etc.

We live in a world where consumers are often presented with a large number of choices across various platforms. Consumers are much more dynamic and hence understanding their ever-changing preferences is of utmost importance. Information needs for businesses are only increasing day by day to understand consumers and identify opportunities. There is a need to employ smarter tools to aid the job of marketer and consumer insight professional. Organizing large volumes of data from heterogeneous sources and building a semantic knowledge system can enable the discovery of competitive intelligence using machine learning. Explore how AI, Bigdata and domain knowledge can come together to build such one-stop knowledge shops.

Sai is the Co-Founder & CTO of Spoonshot. A computer science graduate from IIT (Madras). He has more than 6 years of experience in solving the problems of search and discovery. He worked at Zomato, India's largest food ordering and restaurant discovery platform, as a Software Engineer in search, and re-built its search relevance and ranking models. Later he worked at Myntra, India's biggest online fashion store, as Senior Software Engineer, leading search and style services, working on various aspects, including scaling up its search infrastructure for high revenue days, developing personalized filters based on users fashion preferences, and also conceptualizing a generic search platform.