AI-Testimony, Conversational AIs and Our Anthropocentric Theory of Testimony

ABSTRACT

The ability to interact in a natural language profoundly changes devices’ interfaces and potential applications of speaking technologies. Concurrently, this phenomenon challenges our mainstream theories of knowledge, such as how to analyze linguistic outputs of devices under existing anthropocentric theoretical assumptions. In section 1, I present the topic of machines that speak, connecting between Descartes and Generative AI. In section 2, I argue that accepted testimonial theories of knowledge and justification commonly reject the possibility that a speaking technological artifact can give testimony. In section 3, I identify three assumptions underlying the view that rejects conversational AIs – AI-based technologies that converse, as testifiers: conversational AIs (1) lack intentions, (2) cannot be normatively assessed, and (3) cannot constitute an object in trust relations, while humans can. In section 4, I propose the concept ‘AI-testimony’ for analyzing outputs of conversational AIs, suggesting three conditions for technologies to deliver AI-testimony: (1) content is propositional, (2) generated and delivered with no other human directly involved, (3) the output is perceived as phenomenologically similar to that of a human. I conclude that this concept overcomes the limitations of the anthropocentric concept of testimony, opening future directions of research without associating conversational AIs with human-like agency.

KEYWORDS:

• Testimony
• conversational AIs
• LLM
• artificial intelligence

Acknowledgments

This paper is partly based on my dissertation (2021), submitted to the Graduate Program in Science, Technology and Society at Bar-Ilan University. I thank Boaz Miller, Duncan Pritchard and Noah Efron for commenting on an earlier version of this argument. Additionally, I thank two anonymous reviewers for their valuable and critical comments and suggestions. Views and errors are my own.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1. This passage was brought to my attention by Nickel (2013a), who credits his attention to Salinga and Wuttig (2011).

2. Later on, the work of the Strong Programme in the Sociology of Knowledge was influenced from Shapin’s work. They advocated a theory of knowledge that recognizes testimony as a way for epistemic communities to generate ‎knowledge. This is a result of the ability of testimony to transforms opinions into knowledge – and establish social agreement ‎ (Kusch 2002; for further sociological context of the concept of testimony, see Neges 2018; Freiman and Miller 2021). In fact, it might be that philosophical interest in the concept of testimony was the result of influence from sociology and the history of sciences (Clément 2010), from works such as Latour and Woolgar (1986), Latour (1988), Shapin and Schaffer (1985) and Shapin (1994).

3. In a prior work, I (Freiman 2014) list different related fields that commonly attribute morality to technological artifacts. For current debate about artificial moral agency, see: Behdadi and Munthe (2020); Müller (2020); Firt (2023).

4. I thank an anonymous referee for raising this point and mentioning that others lay the grounds for the view that we may accept one day – algorithms that have achieved the capacity of being moral.

5. Among the considered views are those of Graham (1997, 227) and Coady (1992, 42), both requiring intention to deliver testimony.

6. Lackey uses the term ‘person’ in a broad sense that includes non-human animals (Lackey 2008, fn 13).

7. The proposition ‘the train from Union station will enter platform 4, in 3 minutes’ can preexist as a whole, or can be assembled by an algorithm picking up information from different sources: ‘the train from’ + X +”will enter platform” + Y + ‘in’ + Z + ‘minutes’.

8. The COvid Stay Informed Bot initiative is based on answers from reputable sources. It is available at https://cosibot.org.

Additional information

Notes on contributors

Ori Freiman

Ori Freiman is a Post-Doctoral Fellow at McMaster University’s Digital Society Lab and The Centre for International Governance Innovation’s Digital Policy Hub.