3-2-1 on AI: June Edition

July 5, 2022

Our weekly 3-2-1 on AI newsletter features some of our favorite resources and discussions on the latest AI industry trends, data and thought-provoking quotes, and quick updates on what we’ve been working on.

Check out a summary of last month’s links below and sign up to receive our weekly newsletter straight to your inbox here.

Top picks from the AI Community

  • Financial regulators around the world have generally been more active in regulating industry’s use of AI than adopting it for their own benefit. Opportunities abound, however, for AI-powered regulatory and law enforcement tactics to combat real-world problems in the financial system. (Article)
  • A collection of articles on why organizations need an AI ethics strategy, what’s a good and bad ethics strategy, and how and why to tackle bias head on. (Article)
  • By the end of 2024, Gartner predicts that 75% of the world’s population will have its personal data covered under modern privacy regulations. Once AI regulation becomes more established, it will be nearly impossible to untangle toxic data ingested in the absence of an AI governance program. (Article)
  • 'Connected intelligence' is not a new concept, but it’s becoming more prevalent given that two-thirds of enterprises are adopting AI. A look at how it can be used where humans and machines connect within a digital environment, to share knowledge, and to shape experiences for exponential business growth. (Article)
  • AI, machine learning, and predictive analytics all top the list of hot technology investments for banks in 2022, according to a new Forrester report. (Article)
  • There's a wide range of initiatives to establish ethical principles for AI. Unfortunately, the sheer volume of proposed principles threatens to overwhelm and confuse. This report analyzes several of the highest-profile sets of ethical principles for AI, and reveals an overarching framework consisting of five core principles. (Report)
Image: A Unified Framework of Five Principles for AI in Society

  • Machine learning pioneer Andrew Ng argues that focusing on the quality of data fuelling AI systems will help unlock its full power. An overview on why it's time for 'data-centric' AI. (Article)
  • Jaewon Yang, a Software Engineer at LinkedIn, discusses how the social platform uses Graph Neural Networks (GNNs) and why AI leaders should focus more on GNNs. (Interview)
  • Last week all hell broke loose in the AI world after a Google engineer thought that LaMDA, one of the company’s large language models (LLM), was sentient. Here are some of the lessons learned from the hype and confusion surrounding large language models, and what's truly needed for progress in AI: more transparency, more structure, and more human control. (Article)
  • Applying technologies, like AI, responsibly to augment compliance teams can help both the regulated and regulator to do their job more effectively and collaboratively. A new report by the World Economic Forum, Regulatory Technology for the 21st Century, discusses how organizations can embrace agile, data-driven regulatory solutions to overcome the economic challenges in 2022 and beyond. (Report)
  • Global enterprise AI adoption has reached "critical mass" and is becoming self-sustaining, according to a new report. Around 20% to 25% of enterprises are scaling AI projects across divisions, pointing to maturity of the technology's adoption and commitment to AI projects, with corresponding budgets and resources. (Report)

Image: Omdia Report “AI Market Maturity Survey 2022: Reaching Critical Mass"

  • Cumbersome legacy IT architecture is giving way to living systems that can weave together technologies, data, and talent. These developments have opened up vast possibilities for business strategy innovation — yet only a small number of companies have made a radical leap. A look at how AI can help make strategy more human. (Article)
  • A new whitepaper prepared by Herbert Smith Freehills & UK Finance explores ideas of AI fairness and what these mean for financial services firms, with a focus on the key overlapping regulatory considerations. (Whitepaper)
  • Yann LeCun, chief scientist at Meta’s AI lab and one of the most influential AI researchers in the world, has a bold new vision for the next generation of AI. While he believes we will one day give machines the common sense they need to navigate the world, his vision is far from comprehensive, and may raise more questions than it answers. (Article)
  • Accenture surveyed over 1,600 C-suite executives & data-science leaders from the world’s largest organizations and found that nearly 75% have already integrated AI into their business strategies and reworked their cloud plans to achieve AI success. The report also highlights how these "AI Achievers" are deploying AI solutions to solve problems, spot opportunities, and outperform their peers. (Report)

Image: Accenture Research

AI Quotes We Love

“AI is not something that should be unleashed to derive outcomes from whatever it evolves into. AI should be an extension of human work and used to empower this work – not to undermine it or replace humans.” — Kurt Long
“AI is what I call a general-purpose technology. Like the steam engine or electricity before it, each of these technologies drives waves or cascades of complementary innovations that restructure the way business is run. Ultimately that drives productivity.”  – Erik Brynjolfsson
“Just like our cars are not fully self-driving yet, we still need the human factor in many investment and financial decisions – and for the foreseeable future this will not change.” – Andreas Braun
“AI is not magic. In fact, what I like to describe it as is an immensely powerful tool, but the solutions are ours.”  – Dr. Vivienne Ming
“A holistic approach to AI consists of advancing AI in three areas at once: business transformation, enhanced decision-making, and modernized systems and processes.” – Dr. Anand Rao
“Share the mission: Responsible AI is not just the duty of the AI team but throughout the company.”  – Linda Leopold
“Among executives of the world’s 2,000 largest companies (by market cap), those who discussed AI on their 2021 earnings calls were 40% more likely to see their firms’ share prices increase—up from 23% in 2018.” – Accenture
“4 in 5 organizations cite being able to explain how their AI arrived at a decision as important to their business.”  – IBM
“The global AI market was valued at nearly $59.67 billion in 2021 and is estimated to expand at a CAGR of 39.4%, reaching $422.37 billion by 2028.” – Zion Market Research
“The fair use of AI cannot be considered in siloes, as it requires the application of other AI principles and expertise from across firms.”  – UK Finance

... and a few updates on Apres

Last month we had the pleasure of attending the annual South Summit conference in Madrid. Our Co-Founder & CEO Matt Waite took the stage to present Apres during the Startup Competition, and participated in a panel discussion on AI and decision-making. Check out a full recap of our time at the event here, including a recording of the panel discussion