Your Human-AI Co-Existence (5 Minutes Survey)

The Future of AI starts with You
If we want to achieve a more sustainable and AI-friendly future, we need to start with your individual participation.

Your responses are anonymous and your personal data will not be recorded.

How can you participate?

By filling out this five minute-long and anonymous survey, you can help us in making AI technology more accessible and understandable:

https://forms.gle/DTHmeD9v6XbwXeFn9

Why is that important?

Establishing adaptable and interpretable AI machinery is crucial for individuals and governments to catch up with the speed of technology. Key is not promoting solely development-friendly AI and regulatory overseeing frameworks, but rather working on transparency and readability of technologies through insightful guidelines so that participation for the individual is made possible. This includes the topic of informational self-determination through open legislation frameworks, policies, and ethical guidelines. Both the collective and individual aspect are important for AI technology progression, but a future towards sustainable-friendly AI as an enabler of the 17 sustainable development goals (SDGs) and targets rather than an inhibitor starts with open participation and constant confrontation of the individual with AI technology. One global example that affects us all is ongoing climate change [2], and here we need AI – and the workhorse machine learning (ML) – to contribute to what is clearly the greatest challenge facing humanity. Each and every one of us can contribute to the global challenges of climate change, and we want to explore how AI can help us do that.

[1] Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Felländer, A., Langhans, S. D., Tegmark, M. & Fuso Nerini, F. 2020. The role of artificial intelligence in achieving the Sustainable Development Goals. Nature communications, 11, (233), 1–10, https://doi.org/10.1038/s41467-019-14108-y

[2] Rolnick, D., Donti, P.L., Kaack, L.H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A.S., Milojevic-Dupont, N., Jaques, N. & Waldman-Brown, A. (2022). Tackling climate change with machine learning. ACM Computing Surveys (CSUR), 55, (2), 1–96, https://doi.org/10.1145/3485128

[3] This page is: https://human-centered.ai/2023/09/21/human-ai-5-minutes-survey

 

Thank you very much:

Andreas HOLZINGER, Heimo MUELLER, Jianlong ZHOU, Fang CHEN

Human Centered AI Lab Austria and Human-Centered AI Lab Australia

 

Your Views on ChatGPT in Applications (3 Minutes Survey)

The current development in Large Language Models is good for the machine learning community because it demonstrates the state of the art in statistical learning in an easy to understand way. For example, ChatGPT can fluently answer questions from users. It produces human-like texts with a seemingly logical connection between different sections. According to recent reports, individuals have already used ChatGPT extensively to formulate university essays, write scientific articles with references, debug computer programme code, compose music, write poetry, submit restaurant reviews, create advertising copy and solve exams, co-author magazine articles, and much, much more.
Despite the apparent benefits of ChatGPT, many human users have various ethical concerns about misinformation, transparency, privacy and security, bias, abuse, loss of jobs, lack of originality, over-dependence and even massive job loss.

In our survey, we want to know your views and concerns about ChatGPT so that we can summarise recommendations to users when they use ChatGPT in applications.

Your responses are anonymous and your personal data will not be recorded.

Please take part in our 3 minutes survey:

https://forms.gle/cYMzDyTT7UUP9wRi7

Thank you very much:

Jianlong ZHOU, Heimo MUELLER, Andreas HOLZINGER, Fang CHEN

Human-Centered AI Lab Australia and Human Centered AI Lab Austria

Fairness in Artificial Intelligence Survey

Please take part in our study of Fairness in Artificial Intelligence to help to overcome bias of machine learning

Please take part in our EMPAIA XAI Survey

The Human-Centered AI Lab invites to take part in a causability measurement study to test the new causabilometer

Please take part in our “Causabilometer” Survey

The Human-Centered AI Lab invites to take part in a causability measurement study to test the new causabilometer

Visual Feature Concepts of Intestinal Glands – Darmdrüsen Survey

Please take part in our study in verbal descriptions/explanations of medical concepts relevant for concept machine learning in medical ai

Please take part in our “human explanation survey”

The Human-Centered AI Lab invites the international research community to take part in a human explanation survey

Ten Commandments for Human-AI interaction – Which are the most important?

In the following we present “10 Commandments for human-AI interaction” and ask our colleagues from the international AI/ML-community to comment on these. We will collect the results and present it openly to the international research community.

Kandinsky Challenge: IQ-Test for Machines is online!

The Human-Centered AI Lab (HCAI) invites the international machine learning community to a challenge on explainable AI and towards IQ-Tests for machines