Artificial intelligence has become integral to many businesses today, from virtual assistants to recommendation engines. Underpinning these AI applications is a vibrant field of AI research, increasingly influenced by major technology companies - referred to as "Big Tech."
A new study published in the peer-reviewed Conference on Fairness, Accountability, and Transparency (FAccT 2023) analyzed the presence and impact of Big Tech companies in AI research, specifically focusing on natural language processing (NLP) which powers many language-based AI like chatbots.
Here are some key findings business leaders should know:
- Industry presence in NLP research has risen sharply, with a 180% increase in industry-authored papers from 2017 to 2022. Microsoft, IBM, Meta, Amazon and Google lead in volume.
- 30% of authorships at a major 2022 NLP conference came from Big Tech, versus 20% just 3 years prior in 2019, showing rapid growth.
- Big Tech collaborates extensively with top universities worldwide, but favors proximity - e.g. IBM with University of Melbourne, Meta with Johns Hopkins.
- Students receive substantial industry funding and internships - 65% of European student authors in the study. This expansion to young researchers suggests further growth ahead.
- Industry papers get cited reasonably often, but top universities are comparable. However, Big Tech has an edge in extremely high citations and h-index.
What does this mean for business? First, the tech giants are ramping up investments in NLP research, increasingly recruiting top academics through grants and partnerships. As pioneers in applying AI, their papers and innovations set the pace.
However, there are also concerns around potential monopolization of resources, reduced impartiality in research directions and lack of transparency. As businesses adopt AI, they must balance utilizing the impressive advances coming out of Big Tech labs with maintaining responsible AI practices and monitoring for biases.
The NLP research field is advancing rapidly thanks to substantial industry investments. But we must also encourage academic independence, diversity, and sharing of capabilities where possible. Understanding the presence and incentives of Big Tech in AI research is vital context for business leaders adopting these technologies.
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