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The Behavioral View 4.7: Ethics and AI Development in ABA
Manage episode 430773564 series 2921302
This podcast episode features a discussion on the ethical development and use of AI in the field of Applied Behavior Analysis (ABA). The panel, consisting of CentralReach subject matter experts, explores the potential benefits and challenges of integrating AI into ABA practice. They share insights on how AI can be used to enhance efficiency, support clinical decision-making, and maintain high ethical standards. The conversation also expounds upon the importance of transparency, client consent, and the evolving role of behavior analysts in the context of advancing technologies.
To earn CEUs for listening, click here, log in or sign up, pay the CEU fee, + take the attendance verification to generate your certificate! Don’t forget to subscribe and follow and leave us a rating and review.
Show Notes
References and Resources:
- American Nurses Association, ANA Center for Ethics and Human Rights, (2022). The ethical use of artificial intelligence in nursing practice. www.nursingworld.org
- CentralReach (2024). Ethical AI integration in ABA: A framework for success. https://www.youtube.com/watch?v=uyvBEuUfRbA
- Cedars Sinai, (2024). Pursuing the ethics of artificial intelligence in healthcare. https://www.cedars-sinai.org/newsroom/pursuing-the-ethics-of-artificial-intelligence-in-healthcare/
- Cox, D. J., & Jennings, A. M. (2024). The promises and possibilities of artificial intelligence in the delivery of behavior analytic services. Behavior Analysis in Practice, 17, 123-136.
- Beam, A. L., & Kohane, I. S. (2018). "Big data and machine learning in health care." JAMA, 319(13), 1317-1318.
- Ford, E., et al. (2016). "Extracting information from the text of electronic medical records to improve case detection: a systematic review." Journal of the American Medical Informatics Association, 23(5), 1007-1015.
- Ghafghazi, S., Carnett, A., Neely, L., Das, A., & Rad, P. (2021). AI-Augmented behavior analysis for children with developmental disabilities. Cybernetics Magazine, Vol (10).
- Grote, T., & Berens, P. (2023). A paradigm shift? On the ethics of medical large language models. Bioethics, 38, 38-390. DOI: 10.1111/bioe.13283
- Hosny, A., et al. (2018). "Artificial intelligence in radiology." Nature Reviews Cancer, 18(8), 500-510.
- Panesar, S., et al. (2019). "Machine learning in neurosurgery: a systematic review." Neurosurgical Focus, 46(5), E2.
- Rajkomar, A., et al. (2018). "Scalable and accurate deep learning with electronic health records." NPJ Digital Medicine, 1(1), 1-10.
- Schork, N. J. (2019). "Artificial intelligence and personalized medicine." Cancer Treatment and Research, 178, 265-283.
- Sheikhalishahi, S., et al. (2019). "Natural language processing of clinical notes on chronic diseases: Systematic review." JMIR Medical Informatics, 7(2), e12239.
- Stade, E.C., Stirman, S. W., Ungar, L., Boland, C. L., Schwartz, H. A., Yaden, D. B., Sedoc, J., DeRubeis, R. J., Willer, R., Kim, J. P., & Eichstaedt, J.C. (2024). Toward responsible development and evaluation of LLMs in psychotherapy. Stanford University:Human-Centered Artificial Intelligence
- https://hai.stanford.edu/sites/default/files/2024-06/HAI-Policy-Brief-Responsible-Development-LLMs-Psychotherapy.pdf
- Topol, E. J. (2019). "High-performance medicine: the convergence of human and artificial intelligence." Nature Medicine, 25(1), 44-56.
- Torous, J., & Hsin, H. (2018). "Empowering the digital therapeutic relationship: virtual clinics for digital health interventions." NPJ Digital Medicine, 1(1), 1-3.
- Zhavoronkov, A., et al. (2019). "Deep learning enables rapid identification of potent DDR1 kinase inhibitors." Nature Biotechnology, 37(9), 1038-1040.
46 episodes
Manage episode 430773564 series 2921302
This podcast episode features a discussion on the ethical development and use of AI in the field of Applied Behavior Analysis (ABA). The panel, consisting of CentralReach subject matter experts, explores the potential benefits and challenges of integrating AI into ABA practice. They share insights on how AI can be used to enhance efficiency, support clinical decision-making, and maintain high ethical standards. The conversation also expounds upon the importance of transparency, client consent, and the evolving role of behavior analysts in the context of advancing technologies.
To earn CEUs for listening, click here, log in or sign up, pay the CEU fee, + take the attendance verification to generate your certificate! Don’t forget to subscribe and follow and leave us a rating and review.
Show Notes
References and Resources:
- American Nurses Association, ANA Center for Ethics and Human Rights, (2022). The ethical use of artificial intelligence in nursing practice. www.nursingworld.org
- CentralReach (2024). Ethical AI integration in ABA: A framework for success. https://www.youtube.com/watch?v=uyvBEuUfRbA
- Cedars Sinai, (2024). Pursuing the ethics of artificial intelligence in healthcare. https://www.cedars-sinai.org/newsroom/pursuing-the-ethics-of-artificial-intelligence-in-healthcare/
- Cox, D. J., & Jennings, A. M. (2024). The promises and possibilities of artificial intelligence in the delivery of behavior analytic services. Behavior Analysis in Practice, 17, 123-136.
- Beam, A. L., & Kohane, I. S. (2018). "Big data and machine learning in health care." JAMA, 319(13), 1317-1318.
- Ford, E., et al. (2016). "Extracting information from the text of electronic medical records to improve case detection: a systematic review." Journal of the American Medical Informatics Association, 23(5), 1007-1015.
- Ghafghazi, S., Carnett, A., Neely, L., Das, A., & Rad, P. (2021). AI-Augmented behavior analysis for children with developmental disabilities. Cybernetics Magazine, Vol (10).
- Grote, T., & Berens, P. (2023). A paradigm shift? On the ethics of medical large language models. Bioethics, 38, 38-390. DOI: 10.1111/bioe.13283
- Hosny, A., et al. (2018). "Artificial intelligence in radiology." Nature Reviews Cancer, 18(8), 500-510.
- Panesar, S., et al. (2019). "Machine learning in neurosurgery: a systematic review." Neurosurgical Focus, 46(5), E2.
- Rajkomar, A., et al. (2018). "Scalable and accurate deep learning with electronic health records." NPJ Digital Medicine, 1(1), 1-10.
- Schork, N. J. (2019). "Artificial intelligence and personalized medicine." Cancer Treatment and Research, 178, 265-283.
- Sheikhalishahi, S., et al. (2019). "Natural language processing of clinical notes on chronic diseases: Systematic review." JMIR Medical Informatics, 7(2), e12239.
- Stade, E.C., Stirman, S. W., Ungar, L., Boland, C. L., Schwartz, H. A., Yaden, D. B., Sedoc, J., DeRubeis, R. J., Willer, R., Kim, J. P., & Eichstaedt, J.C. (2024). Toward responsible development and evaluation of LLMs in psychotherapy. Stanford University:Human-Centered Artificial Intelligence
- https://hai.stanford.edu/sites/default/files/2024-06/HAI-Policy-Brief-Responsible-Development-LLMs-Psychotherapy.pdf
- Topol, E. J. (2019). "High-performance medicine: the convergence of human and artificial intelligence." Nature Medicine, 25(1), 44-56.
- Torous, J., & Hsin, H. (2018). "Empowering the digital therapeutic relationship: virtual clinics for digital health interventions." NPJ Digital Medicine, 1(1), 1-3.
- Zhavoronkov, A., et al. (2019). "Deep learning enables rapid identification of potent DDR1 kinase inhibitors." Nature Biotechnology, 37(9), 1038-1040.
46 episodes
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