Five missing elements in the AI revolution
Artificial Intelligence (AI) is rapidly expanding and affecting every aspect of our daily lives. We have no doubt come a good distance on what is indeed a very long AI road.
But many dangers and problems will still persist if we don't look past the hype and focus on key challenges that lie ahead. Here's a synopsis of five needs and challenges from my recent post in Fast Company magazine.
1. Applying AI
Data scientists are overwhelmed by the complexity and quantity of data, while line-of-business executives are underwhelmed by the tangible output of data scientists.
Need: A clear set of high-value use cases and data sources by industry and process domains where AI can create demonstrable business value.
2. Building AI
We are at risk of graduating data scientists capable of designing an algorithm that is mathematically elegant, but doesn’t make strategic sense for the business.
Need: Graduates with multi-disciplinary training in data science as well as strategy, design, insights, and change management.
3. Testing AI
AI software learns in different, nuanced ways each time it is trained.
Need: New types of software testing that start with an initial "ground truth" and then verify whether the AI system is doing its job.
4. Governing AI
Algorithm development has so far been driven by the goal of improving performance, at the expense of credibility and traceability.
Need: AI systems that are not opaque "black boxes." AI systems should be manageable and able to clearly explain their actions. This issue will only get bigger as AI leads to new complex processes and longer chains of responsibility.
5. Experiencing AI
AI isn’t just software. The quality of the user experience determines both the usefulness of the product and its rate of adoption.
Need: Design of AI systems that provide delightful micro-interactions between man and machine. Quality of the user experience will drive product adoption and trust.
Click here to view my full post titled "What's still missing from the AI revolution" on Fast Company.
About the Author:
Manoj Saxena is the Executive Chairman of CognitiveScale and a founding managing director of The Entrepreneurs’ Fund IV, a $100m seed fund focused exclusively on the cognitive computing and machine intelligence market with eight active investments.
Previously, he was IBM’s first general manager of IBM Watson (2011-14), where his team built the world’s first cognitive systems for healthcare, retail, and financial services.
In his spare time he competes in long distance automobile races in pre-war, classic, and contemporary cars. More at www.saxenaracing.com