The political ideology of conversational AI: Converging evidence on ChatGPT’s pro-environmental, left-libertarian orientation

Hartmann, Jochen; Schwenzow, Jasper; Witte, Maximilian

doi:10.2139/ssrn.4316084

Cited by 68 publications

(40 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is interesting to note that ChatGPT's solutions address sustainability, resiliency, affordability, and multi-modality, which is in line with a recent empirical study that revealed ChatGPT's pro-environmental and leftlibertarian orientations (Hartmann, Schwenzow, and Witte 2023). Transport researchers might be relieved that ChatGPT did not suggest "awful" solutions, such as highway expansions or cutting public transit services.…”

Section: Resultssupporting

confidence: 62%

How does ChatGPT Introduce Transport Problems and Solutions in North America?

Kim¹,

Lee²

2023

Findings

View full text Add to dashboard Cite

How does ChatGPT introduce transport problems and solutions in North America? By analyzing ChatGPT’s answers to four prompts related to transport issues and solutions in the United States and Canada, our results reveal that ChatGPT’s answers generally align well with transport researchers’ expectations. However, ChatGPT’s capability may be limited in providing trustworthy or sound solutions because of the potential issues (e.g., geographic biases, inaccuracy) in its training data. ChatGPT might be a decent starting point for discussing transport issues and solutions, but one should be aware of its limitations.

show abstract

Section: Resultssupporting

confidence: 62%

How does ChatGPT Introduce Transport Problems and Solutions in North America?

Kim¹,

Lee²

2023

Findings

View full text Add to dashboard Cite

show abstract

“…These biases may arise from the fact that ChatGPT models have been trained on human-generated text and reinforcement learning from human feedback to better align with human values [74,75]. In particular, ChatGPT outputs could potentially contain biases toward political leanings [76–79]. These possible biases are unlikely to have affected the results of Study 1, because ChatGPT was tasked to provide numeric scores and not to generate new ideas.…”

Section: Discussionmentioning

confidence: 99%

Using ChatGPT for human–computer interaction research: a primer

Tabone,

de Winter

2023

R. Soc. open sci.

View full text Add to dashboard Cite

ChatGPT could serve as a tool for text analysis within the field of Human–Computer Interaction, though its validity requires investigation. This study applied ChatGPT to: (1) textbox questionnaire responses on nine augmented-reality interfaces, (2) interview data from participants who experienced these interfaces in a virtual simulator, and (3) transcribed think-aloud data of participants who viewed a real painting and its replica. Using a hierarchical approach, ChatGPT produced scores or summaries of text batches, which were then aggregated. Results showed that (1) ChatGPT generated sentiment scores of the interfaces that correlated extremely strongly ( r > 0.99) with human rating scale outcomes and with a rule-based sentiment analysis method (criterion validity). Additionally, (2) by inputting automatically transcribed interviews to ChatGPT, it provided meaningful meta-summaries of the qualities of the interfaces (face validity). One meta-summary analysed in depth was found to have substantial but imperfect overlap with a content analysis conducted by an independent researcher (criterion validity). Finally, (3) ChatGPT's summary of the think-aloud data highlighted subtle differences between the real painting and the replica (face validity), a distinction corresponding with a keyword analysis (criterion validity). In conclusion, our research indicates that, with appropriate precautions, ChatGPT can be used as a valid tool for analysing text data.

show abstract

“…Examples exist across various topics and have been documented with many successful and prominent bypasses of these content restrictions. 36 Compliance bias represents additional substantial concern, whereby the constructed text/data provided by the AI system are of such perceived high quality, with the assumed accuracy implied by the large data set that it is "believed" as fact despite potential errors. These generated "hallucinations" are coherent collections of mainstream data that simply seem factual but are fictional.…”

Section: Biasmentioning

confidence: 99%

Ethical Considerations of Artificial Intelligence in Health Care: Examining the Role of Generative Pretrained Transformer-4

Sheth,

Baker,

Prescher

et al. 2024

J Am Acad Orthop Surg

View full text Add to dashboard Cite

The integration of artificial intelligence technologies, such as large language models (LLMs), in health care holds potential for improved efficiency and decision support. However, ethical concerns must be addressed before widespread adoption. This article focuses on the ethical principles surrounding the use of Generative Pretrained Transformer-4 and its conversational model, ChatGPT, in healthcare settings. One concern is potential inaccuracies in generated content. LLMs can produce believable yet incorrect information, risking errors in medical records. Opacity of training data exacerbates this, hindering accuracy assessment. To mitigate, LLMs should train on precise, validated medical data sets. Model bias is another critical concern because LLMs may perpetuate biases from their training, leading to medically inaccurate and discriminatory responses. Sampling, programming, and compliance biases contribute necessitating careful consideration to avoid perpetuating harmful stereotypes. Privacy is paramount in health care, using public LLMs raises risks. Strict data-sharing agreements and Health Insurance Portability and Accountability Act (HIPAA)-compliant training protocols are necessary to protect patient privacy. Although artificial intelligence technologies offer promising opportunities in health care, careful consideration of ethical principles is crucial. Addressing concerns of inaccuracy, bias, and privacy will ensure responsible and patient-centered implementation, benefiting both healthcare professionals and patients.

show abstract

The political ideology of conversational AI: Converging evidence on ChatGPT’s pro-environmental, left-libertarian orientation

Cited by 68 publications

References 18 publications

How does ChatGPT Introduce Transport Problems and Solutions in North America?

How does ChatGPT Introduce Transport Problems and Solutions in North America?

Using ChatGPT for human–computer interaction research: a primer

Ethical Considerations of Artificial Intelligence in Health Care: Examining the Role of Generative Pretrained Transformer-4

Contact Info

Product

Resources

About