BMF Collaborative Project 16: Belief about AI’s mind and self-prolongation

AISDL Team
Email: aisdl_team@mindsponge.info

February 11, 2023

1. Project description

1.1. Background

Does artificial intelligence (AI) have a mind of its own? This is indeed an intriguing question, especially considering the rapid advancement of information technology. How we humans establish our personal beliefs about this matter is likely based on what we know about biological systems. One of the most fundamental aspects of the “mind”, as we know it, is the natural desire to exist/function.

1.2. Main objectives

This study will examine how the belief about AI’s self-prolongation may affect the belief about AI having a mind of its own. Additionally, the factor of familiarity with AI interactions will be examined for any possible moderating effect.

1.3. Materials

The research project will employ a dataset of 266 US residents collected in 2018 [1].

The research project will follow the Bayesian Mindsponge Framework (BMF) [2,3]. The bayesvl R package will be employed for statistical analyses [4].

1.4. Main findings

The analysis result shows that the more a person believes that AI seeks continued functioning, the more he/she believes that AI has a mind of its own. However, this effect is lessened when considering one’s familiarity with personally interacting with AI. In other words, among people strongly believing that AI seeks continued functioning, those who are more familiar with AI will be less likely to believe that AI has a mind of its own.



Figure: Density distributions of the analytical model’s posterior coefficients

Data and codes used in this initial analysis were deposited at: https://osf.io/qazn6/

2. Collaboration procedure

Portal users should follow these steps to register to participate in this research project:

• Create an account on the website (preferably using an institution’s email).
• Comment your name, affiliation, and your desired role in the project below this post.
• Patiently wait for the formal agreement on the project from the AISDL mentor.

If you have further inquiries, please contact us at aisdl_team@mindsponge.info.

If you have been invited to join the project by an AISDL member, you are still encouraged to follow the above formal steps.

All the resources for conducting and writing the research manuscript will be distributed upon project participation.

AISDL mentor for this project: Tam-Tri Le

AISDL members who have joined this project: Minh-Hoang Nguyen, Quan-Hoang Vuong, and La-Viet Phuong.

The research project strictly adheres to scientific integrity standards, including authorship rights and obligations [5], without incurring an economic burden at participants’ expenses [6].

References

[1] Shank DB, Gott A. (2019). People’s self-reported encounters of Perceiving Mind in Artificial Intelligence. Data in Brief, 25, 104220.

[2] Nguyen MH, La VP, Le TT, Vuong QH. (2022). Introduction to Bayesian Mindsponge Framework analytics: An innovative method for social and psychological research. MethodsX, 9, 101808.

[3] Vuong QH, Nguyen MH, La VP. (2022). The mindsponge and BMF analytics for innovative thinking in social sciences and humanities. De Gruyter.

[4] La VP, Vuong QH. (2019). bayesvl: Visually Learning the Graphical Structure of Bayesian Networks and Performing MCMC with ‘Stan’. The Comprehensive R Archive Network.

[5] Vuong QH. (2020). Reform retractions to make them more transparent. Nature, 582(7811), 149.

[6] Vuong QH. (2018). The (ir)rational consideration of the cost of science in transition economies. Nature Human Behaviour, 2(1), 5.