GENERATIVE AI

Policy: Given the potential impact and implications, regulation is necessary to address ethical concerns, ensure privacy and data protection, mitigate potential biases or discriminatory outcomes and maintain accountability [3]. The latter sentiment is mirrored not only by public actors, but also by the private sector, as the Institute for the Future of Life alongside industry experts published an open letter in early 2023 to call for a pause of giant AI experiments [6]. However, regulation in the US on GenAI is still quite nascent, congress has passed several bills that focus on governing AI but most measures either seek to explore the topic or only affect how the government itself are using it [18][19]. Senator Chuck Schumer is working on a framework to regulate AI on a national level, but in general lawmakers on a global scale are struggling to keep up with the developments of the technology [17]. In California lawmakers seek to be first in regulating business uses of GenAI and recently introduced A.B. 331, which is a framework for the regulation of “Automated Decision Tools”. It aims at monitoring how employers and industries use these tools. Compared to previous bills this is more far-reaching, as it targets discrimination from AI in everything from employment, financial services, education and more [19].

Entrepreneurship: Y Combinator’s Summer 2022 batch included 11 startups focused on GenAI. However, in just six months, their Winter 2023 (W23) cohort saw a significant increase, with 59 GenAI start-ups, comprising 22% of the total 272 companies in the cohort. Garry Tan, Y Combinator’s president and CEO, stated in February that generative AI is “the new frontier” [8][9]. Y Combinator is a pioneering Silicon Valley based accelerator that each year invests in a large number of start-ups, to go through their intensive three-month accelerator and coaching program, with the aim to get them ready for pitching to US investors. By now they have funded 4.000 start-ups with a combined valuation of 600 billion USD. A few of the start-ups that later had huge success are Airbnb, Stripe, Dropbox, Instacard, Reddit, Flexport, Cruise and many more [14][15][16].

Investment: In 2022, GenAI garnered substantial investor interest, with USD 2.65 billion invested across 110 deals. Most companies had not raised Series A funding or received outside equity. Generative interfaces experienced the most momentum, with a remarkable 692% funding increase from 2021 to 2022 [8][9]. In Q1 of 2023, generative AI start-ups have raised roughly USD 1.7 billion across 46 deals [10] marking the ongoing interest in the field. 

Corporate: The applications are endless and the potential massive, but for a corporate looking to design, deploy, and scale GenAI it is important to build the right governance framework and ensure responsible use [3]. There are two primary implementation approaches depending on the intended application. The first option is Model-as-a-Service via API integration, using externally managed larger models like ChatGPT, acting as a universal tool. The second is an open-source software solution to internally run smaller models, focused on very specific tasks [1].

Academia: In efforts to capitalize on the rapid AI innovation and supporting further research, the US government is opening seven new AI labs. Aimed at advancing the development of AI within six research agendas; 1) trustworthy AI, 2) intelligent agents for cybersecurity, 3) climate-smart agriculture and forestry, 4) neural and cognitive foundations of AI, 5) AI for decision-making, and 6) AI-augmented learning. The laboratories will be an interdisciplinary collaboration between top AI researchers supported by co-funding from different US governmental departments. They will be based out of seven different universities around the US; 1) University of Minnesota, 2) University of Columbia, 3) UC Santa Barbara, 4) Carnegie Mellon University, 5) University of Buffalo, 6) University of Illinois and 7) University of Maryland [11].