š¬ Original article by Abhinav Raghunathan, the creator of EAIDB who publishes content related to ethical ML / AI from both theoretical and practical perspectives.
This article is a part of our Ethical AI Startups series that focuses on the landscape of companies attempting to solve various aspects of building ethical, safe, and inclusive AI systems.
Thereās no questioning the ubiquity of artificial intelligence (AI). Thereās no argument that can be made that AI is not at the core of Western society, part of the fabric of our everyday lives.
Over the past three decades, a greater emphasis has been placed on growth, on scale, on the positive potential of AI. It is now used constantly in every context as a solution to every problem. But times have changed. Only recently have thought leaders in the space transitioned the thinking away from unparalleled growth (AI has grown enough) and towards controlling AI riskāāāthe negative potential for AI to perpetuate bias, generate disinformation, and much more. When AI fails, it fails explosively.
Solutions came in droves as soon as it became clear to investors, governments, and business owners that AI risk can be dangerous and costly and that consumer trust (which directly translates to profit) is increasingly hard-earned in a world with so many cases of AI run rampant. Many ethical AI vendors are in their infancyāāāstartups attempting to combat the wide world of irresponsible AI. The ethical AI space itself is a relatively small blip on the funding worldsā radar: underrepresented, underfunded, and underrated.
This column is a comprehensive guide to the five different categories of āEthical AIā startups and the dynamics between them. We will analyze trends, make predictions, and identify the strengths and weaknesses of each category of this fascinating and critical startup ecosystem.
The Ethical AI Database (EAIDB)
Everyone throughout the company lifecycle (from founders to investors to end users) are gradually becoming more aware and more receptive to transforming AI into a more ethical version of itself. To accelerate the conversation, the industry must be made more transparentāāāthe companies recognized, the founders and investors alerted, the policymakers aware. This is where EAIDB comes into play.
EAIDB is a live database of startups that either provide tools to make existing AI systems ethical or build products that remediate elements of bias, unfairness, or āunethicalnessā in society. EAIDB also publishes quarterly market maps / reports and spotlights constituent companies.
Preview of the EAIDB Market Map for Q1 2022.
Startups that dedicate their services and products to enabling responsible technology are broken into five categories:
- Data for AI
- ModelOps, Monitoring, & Observability
- AI Audits, Governance, Risk, & Compliance
- Targeted AI Solutions & Technologies
- Open-Sourced Solutions
In subsequent pieces, each of these five categories will be explored in detail.
Growth + Trends
The data EAIDB has collected on its 140+ ethical AI startups shows that both investor and founder interest is growing. As of 2016, only 28 of EAIDBās constituents were active. In 2022, we recorded 153 active companies (a total growth of about 446% and a CAGR of about 32.7%). Clearly, this space is profitable and motivation to make technology responsible exists.
Total active Ethical AI startups by year.
A category-wise breakdown reveals that, in recent years, the buzz has been mostly around data-related operations (āData for AIā) and GRC (āAI Audits, Governance, Risk, & Compliance).
Growth in categories of EAIDB by founding year.
Most thought leaders in this space agree that motivation is only increasingāāāwhether through fear or through willingness. Policy changes made by those like the New Zealand and Scottish governments, the State of New York and California, and others will surely drive a stronger business need to mitigate AI risk. There is sound logic behind the claim that the āethical AIā sector might approximate the growth curves of the privacy boom of the mid-2010s or the cybersecurity boom in the late-2000s. Only time will tell.
The next issue of Ethical AI Startups will cover the first of our categories: Data for AI.
To learn more about EAIDB, visit the dedicated website at https://eaidb.org.