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
- While the concept of “human-centered design” is hardly new, efforts are growing to build inclusive AI products, or algorithmic systems which are created with input from people who are not on AI/ML development teams. This whitepaper provides four guiding principles for building inclusive AI. (Whitepaper)
- Last year, the UK Government published its National AI Strategy, setting out a vision to strengthen the UK’s position as an AI and science superpower over the coming decade. Now, the UK Government has put forward an Action Plan to guide this strategy. (Guide)
- Financial institutions follow strict regulatory policies, and any incorrect decision can cost millions of dollars and damage consumer confidence. It is imperative for financial companies to subject their AI models to rigorous, dynamic model risk management and validation. A look at where AI in financial services is extensively used and why explainable models are crucial in each scenario. (Article)
- Iason Gabriel is a research scientist at DeepMind and a former lecturer in political & moral philosophy at Oxford University. In this conversation, he discusses how and why AI is different from other technologies; the problem of value alignment in AI; what political philosophy can tell us about how to build ethical AI systems; and much more. (Podcast)
- The new 'State of AI in Africa Report' offers analytical insight into the growing AI sector in Africa, a topic that has not been fully explored up until now. The unique report contains statistics and trends, offering an in-depth look at key factors and communities driving the ecosystem across the continent. (Report)
- The Stanford Institute for Human-Centered Artificial Intelligence asked the community what books on AI they recommend. Check out their recommendations and add some to your summer reading list. (Article)
- The Algorithmic Accountability Act was reintroduced in April 2022 in both the US House and Senate. AI bias, audit, and reporting are all key factors in the new act. Here's what tech leaders need to know and do now. (Article)
- The machines are coming for financial crime—or at least machine learning is—as an explosion in AI offerings is driving a shift in what enforcers could expect from financial institutions and corporations. How banks are turning to AI to help dodge the enforcement spotlight. (Article)
- Financial organizations that embrace digital and analytics as necessary instruments to augment decision making will have an enormous advantage over those that continue to rely on personal judgment and incomplete data. Already, the adoption of digital technology at scale is creating a new breed of investors who are faster and better at identifying and evaluating opportunities. (Article)
- A new report, 'AI Startups and the Fight against Mis/Disinformation,' interviewed 20 AI startups to get an update on the role of AI in the fight against mis/disinformation and the evolution of the market for tech-based solutions, many of which use some form of AI and machine/deep learning for content moderation, media integrity, and verification. (Report)
- Wondering where AI regulations stand in each U.S. state? The Electronic Privacy Information Center (EPIC) released 'The State of State AI Policy,' a roundup of AI-related bills at the state and local level that were passed, introduced, or failed in the 2021-2022 legislative session. (Article)
- The financial industry AI love fest persists due to its power to tackle risk management and other industry-specific objectives. Wealth management firms were found to be particularly high on AI, while insurance companies use the technology at a lesser rate, according to a new study, 'The Future of the Data-Driven Workplace.' (Report)
- As we enter the second half of the year, it’s time to take stock of where we’ve come this year in big data, advanced analytics, and AI, and assess where we’re likely to go next. A look at five predictions for the remainder of the year. (Article)
- Gartner recently published a new ebook, 'The Future of Decisions,' that outlines the process of dissecting and reengineering decisions to both separate human input from machine involvement, as well as enabling the two to work in unison. (Ebook)
- In a recent AI Ethics survey by IBM, 85% of IT professionals agreed that consumers are more likely to choose a company that's transparent about how its AI models are built, managed, and used. An overview of how explainable AI is key to addressing concerns about understanding and trusting AI's results. (Article)
AI Quotes We Love
“40% of US enterprises have reached the higher stages of AI maturity, which means they have moved from the theoretical and experimentation phases to seeing tangible results and return on investment for AI.” – XLT Report
“Effective and impactful AI can only happen when technology and humans work in symbiosis, and trust must exist for this relationship to be harmonious.” – Josh Feast
“By 2030, AI is estimated to give an additional economic output of around €11 trillion, increasing global GDP by about 1.2% annually.” – European Parliament
“You need to have a strong, ethical approach to your use of data, a strong commitment to really truthful and accurate and good quality of information, so you don’t have the wrong information in your products and solutions.” – JoAnn Stonier, Chief Data Officer, Mastercard
“As more and more AI is entering into the world, more and more emotional intelligence must enter into leadership.” ― Amit Ray
“Only 14% of banks have a specific AI governance framework.” – McKinsey
“Banks worldwide are expected to spend an additional $31 billion on AI embedded in existing systems by 2025 to reduce fraud.” – IDC
“The ethical integration of AI with human values and emotions is the foundation of future AI.” – Amit Ray
