SURVEY – THE SEVEN DEADLY SINS OF AI IN MEDICINE

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SURVEY – THE SEVEN DEADLY SINS OF AI IN MEDICINE

We invite you to participate in a crucial survey examining the key ethical challenges in medical AI.

Your insights are invaluable in shaping a future where AI enhances healthcare responsibly.

This survey will take only approx 4 minutes of your time, yet it addresses issues of paramount importance that affect us all.

https://ec.europa.eu/eusurvey/runner/seven-sins-of-medical-ai

Thank you very much,

Heimo MUELLER, Vimla L. PATEL, Edward H. SHORTLIFFE, Andreas HOLZINGER

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

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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)

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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

Usability Evaluation of Interactive XAI platform for Graph Neural Networks

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Lack of trust in artificial intelligence (AI) models in medicine is still the key blockage for the use of AI in clinical decision support systems (CDSS). Although AI models are already performing excellently in medicine, their black-box nature entails that it is often impossible to understand why a particular decision was made. In the field of explainable AI (XAI), many good tools have already been developed to “explain” to a human expert, for example, which input features influenced a prediction. However, in the clinical domain, it is essential that these explanations lead to some degree of causal understanding by a clinician in the context of a specific application. For this reason, we have developed an interactive XAI platform that allows the domain expert to ask manual counterfactual (“what-if”) questions. CLARUS allows the expert to observe how changes based on their questions affect the AI decision and the corresponding XAI explanation [1].

Please help us now with a usability evaluation and spend 10 minutes and go through this:

https://survey.medunigraz.at/index.php/368984?lang=en

and please fill out all fields (please include all feedback you think is necessary into the boxes),

please note that there will be TWO Windows open: one is the application and one is the questionaire,
so maybe it is better to open them in two separate windows for your convienience,

thank you very much

[1] https://doi.org/10.1101/2022.11.21.517358

Human-Centered AI for smart farming BOKU Tulln March, 9, 2023

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On March, 9, 2023 at the BOKU Tulln, we were guest speakers at the traditional Schlumberger lectures. For us a wonderful opportunity to show what Human-Centered AI can do for smart farming. Thanks to the organizers Michaela Griesser and Astrid Forneck from the Department of Crop Sciences (DNW) lead by Hans-Peter Kaul. Looking forward to help to discover the causality of berry shrivel (Traubenwelke) with methods from deep geometric learning for knowledge discovery from point cloud data.

Inaugural Lecture Andreas Holzinger Human-Centered AI

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The inaugural lecture of Andreas Holzinger on Monday, Nov, 7, 2022, 18:00 on Human-Centered AI is open to the public – you are cordially welcome

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Open Postdoc Position “Artificial intelligence for smart forest operations”

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We continue to build up our HCAI-Lab in an absolutely cool environment with exciting Artificial Intelligence topics.

Cyber-physical systems, robotics, sensor technology, data management in general, and methods of artificial intelligence (Al) and machine learning (ML) with applications to smart farm and forest operations are of increasing interest.

We seek an postdoctoral research associate in AI/machinelearning for Forest Operations, Reference Code 184

Please note the following required qualifications:

  • Doctorate degree / PhD in Computer Science/Informatics or equivalent
  • Language skills: German and English
  • Evidence of a very active publication record is required
  • Extensive teaching experience in Al/machine learning and data science
  • Experience in developing deep learning models to solve complex problems

please apply here:

https://euraxess.ec.europa.eu/jobs/838860

Note: We regret that we cannot reimburse applicants travel and lodging expenses incurred as part of the selection and hiring process.

We constantly seek to increase the number of female faculty members. Therefore qualified women are strongly encouraged to apply. In case of equal qualification, female candidates will be given preference unless reasons specific to an individual male candidate tilt the balance in his favour. People with disabilities and appropriate qualifications are specifically encouraged to apply.

Cross Domain Machine Learning and Knowledge Extraction Conference

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Great Cross Domain Machine Learning and Knowledge Extraction Conference in Vienna

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July, 5, 2022 BOKU HCAI AI for smart forestry workshop

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Our new BOKU Human-Centered AI Lab Vienna Area in beautiful Tulln/Donau, Lower Austria, is taking shape and our mission to connect Lower Austria with Vienna starts: Our first visitors in Lower Austria were from Lower Austria. In our little workshop with colleagues from the University of Applied Sciences St. Pölten we discussed cool topics of digitaltransformation for smart agriculture and forestry, especially some challenges and future aspects of artificial intelligence/machine learning for solving problems in smart forestry, e.g. road trafficability with the help of cyber-physical systems and sensors, or the grand challenge and hot topic of “embodied intelligence”, e.g.: “move to timber – grab the timber – move back to truck” which is easy for humans, but practically impossible for current artificial intelligence – and one solution is in making use of the human-in-the-loop, see our very recent position paper:

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Open PhD Positions “Artificial intelligence for smart forest operations”

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We are building up our HCAI-Lab in an absolutely cool environment with exciting Artificial Intelligence topics.

Cyber-physical systems, robotics, sensor technology, data management in general, and methods of artificial intelligence (Al) and machine learning (ML) with applications to smart farm and forest operations are of increasing interest.

Work tasks include independent execution and analysis of scientific experiments in Al/machine learning with a focus on smart farm and forest operations, writing scientific publications in a team and presentations as well as lecturing and administrative duties. The completion of a PhD within the position`s timeframe is desired.

Required Skills and qualifications:

  • Master degree in computer science/Informatics
  • Good command of German (spoken) and English (spoken and writing)
  • Proven skills in Python

Desirebable skills and qualifications:

  • Practical experience in conducting experiments in Al/Machine Learning
  • Interest in Cyber-physical systems and embodied intelligence
  • Ability to communicate and work as part of a team

University of Natural Resources and Life Sciences Vienna seeks to increase the number of its female faculty and staff members. Therefore qualified women are strongly encouraged to apply. In case of equal qualification, female candidates will be given preference unless reasons specific to an individual male candidate tilt the balance in his favour.

People with disabilities and appropriate qualifications are specifically encouraged to apply.

Please send your job application incl. motivation letter, your CV, and at least one of your publications in ONE single pdf file,
with the code BY22FAB in the email header (to bypass the automatic spam filter) directly to andreas.holzinger AT human-centered.ai

We regret that we cannot reimburse applicants travel and lodging expenses incurred as part of the selection and hiring process.