by Ciaran Daly


NEW YORK – The ethical and effective implementation of AI is the key technology priority for global business and enterprise, as the attendees of The AI Summit New York learnt today.

The Javits Center opened its doors to 3500+ delegates, 300+ senior enterprise and technology keynote speakers, and the latest in AI and robotics technology in the bumper third New York edition of the world-leading conference and exhibition series.

Notably, the Summit hosted keynotes from members of the global Fortune 100 C-Suite from companies including IBM, Microsoft, Bank of America, Forbes, Google, and many more. A particular highlight was Genpact and Envision Virgin Racing’s unveiling of an AI-powered Formula E car, which was covered exclusively here.

As the Summit wraps up its first day, let’s take a look at some of the key insights:

  1. AI implementation is emerging as a key priority for business

A key theme throughout the day was that AI is no longer hypothetical. Its implementation is a core priority for businesses looking to get ahead.

Part of the reason for this, argued Beth Smith, General Manager of IBM Watson, is that AI makes it possible for companies to harness the power of the data they already have. “We’re in an era of exponential learning,” she told the packed-out auditorium. “AI is allowing us to unlock knowledge from all of the data that exists in the world – and 80% of data is inside companies.”

Sowmya Gottipati, Vice President of NBC Media Labs, meanwhile made the case for the power of real-world AI use cases. She explained that initial insights from her team demonstrated to her the importance of using AI and machine learning to address business needs – and from there, AI projects grew exponentially across the network’s channels.

“Business teams often don’t always know what is meaningful for them,” Gottipati said. “They may understand that AI can provide them with some interesting data, but they might not know how that data can be leveraged to solve a business problem or enhance consumer experience. This is really a hand-in-hand process, in which you have to work in partnership with the business team [to explain] the technologies and their limitations, and also help them arrive at use cases with which they can actually solve a business problem. You have to be there for that journey.”

2. The ethical deployment of AI is a rapidly growing concern for businesses

As the deployment of AI increases, consumer trust is growing precarious. This was a common theme throughout the day, as the speakers explored different ways of building trust, transparency, and accountability into their AI solutions.

“None of us get the option of separating ourselves from the impact of the tech we’re creating,” argued Cathy Bessant, Chief Operations and Technology Officer for Bank of America. “Responsible AI is not about what we can do, but what we should do.”

David Carmona, General Manager of Microsoft AI, added: “If we want AI to go beyond organizations, we need to make sure society trusts AI. It is imperative as an industry. We need to create responsible AI so we can bring trust to the technology.”

Some speakers argued that ethical considerations are integral to a thriving AI ecosystem – as without consumer trust and consent, adoption can go nowhere. Sana Khareghani

“Being mindful of security/privacy doesn’t mean you can’t have a thriving ecosystem. However, with ability for AI to take human bias and magnify it, it’s important to build security and ethics into the algorithm,” said Sana Khareghani, the Head of the UK Government Office for AI. “It’s too early to worry about AI becoming the Terminator. Instead, worry about diversity. More diversity of thought is needed to represent the population in AI algorithms.”

3. Effective use of AI means getting to grips with real-world data

Perhaps it is reflective of the practical concerns dominating AI discourse today that data quality was noted as a significant issue by all speakers.

Bastian Janmaat, CEO of Oracle’s Datafox, made the case that AI investments must be matched with data investments: “How? Do your diligence. Pursue applied AI, incorporate human-in-the-loop, and keep data integrity high. Feeding garbage data into fancy algorithms will [produce] garbage results.”

In an exclusive interview with AI Business, the CEO of Appen, Mark Brayan, meanwhile argued that mitigating the quality of datasets will be the core consideration for companies looking to implement AI in 2019. Mark explained that the company leverages over 40,000 staff worldwide specifically to this end, with the goal of enabling enterprises to hit the ground running and start applying AI solutions without the need for in-house data scientists.

This is just one example of a push to help enterprises improve their data quality for AI. The recently-announced IBM Watson Academy is designed to train employees as citizen data scientists in order to make the most out of AI. These trends highlight that the challenge of data is inextricably linked to the issue of AI skills, which continue to face huge demand.

Stay tuned for all our exclusive video interviews, insights, and content from The AI Summit in the coming weeks.