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On Demand

Parting the Fog of Techno-Determinism: The Future of Social Work and Artificial Intelligence (On Demand)

Total Credits: 1.5 including 1.5 Category II CEs

200 Adults, Couples & Families |  600 Leadership and Management |  700 Professional Growth & Development |  Special Offers |  OnDemand
Clara Berridge |  John Bricout |  Lauri GoldKind
1 Hour 33 Minutes
Audio and Video


Join us to learn about artificial intelligence and social work practice. We will provide an overview of what artificial intelligence is, explore several areas of social work practice where artificial intelligence tools are being deployed, and conclude with a discussion of ethical implications for these new technologies.

Recorded on April 20, 2023



* If you are purchasing CE, a brief quiz completion is mandatory in order to obtain a certificate. 

* On-Demand workshops are worth Category II CEs (for Maryland Social Workers)

* You have thirty (30) days of access after registration



Clara Berridge Related Seminars and Products

Clara Berridge, PhD, MSW, is Associate Professor and Katherine Hall Chambers Scholar in the School of Social Work at the University of Washington, where she is Adjunct Associate Professor in the Evans School of Public Policy and Governance and Core Faculty in the Disability Studies Program. Her research examines the ethical and policy implications of data-intensive technologies for elder care and how to promote sociotechnical practices in ways that do not marginalize, isolate, or diminish their participants.  

John Bricout Related Seminars and Products

John Bricout, PhD, MSW, is a professor and interim director in the University of Minnesota, School of Social Work (UMN SSW). He also serves as co-director of the interdisciplinary workforce development and research lab (WDRL) in the UMN College of Education and Human Development. Professor Bricout’s research examines the socio-cultural aspects of participatory, ethical design for robotics and intelligent assistive technologies to enhance the capabilities and well-being of people with disabilities. He is a network co-lead for the Grand Challenges in Social Work Harnessing Technology for the Social Good.  

Lauri GoldKind Related Seminars and Products

Lauri Goldkind, PhD, LMSW is an associate professor at Fordham’s Graduate School of Social Service and the Editor in Chief of the Journal of Technology in Human Services. Goldkind’s is on a quest is to understand how digital technologies are changing life on earth and beyond. Dr. Goldkind’s current research has two strands: data justice and its practical applications for individuals and communities and information and communication technologies (ICT) tools in human services nonprofits. She has a robust network of community partners in New York City and internationally, including the International Federation of Settlement Houses, United Neighborhood Houses and Caritas Macau. She holds an M.S.W. from SUNY Stony Brook with a concentration in planning, administration, and research and a PhD from the Wurzweiler School of Social Work at Yeshiva University. Dr. Goldkind was in residence at the United Nations University Institute on Computing and Society, located in Macau, SAR, China from June to August 2017. Goldkind’s book, Digital Social Work, containing technology case studies for social workers, was edited with colleagues Lea Wolf and Paul Freddolino and published by Oxford University Press in 2018. She is a network co-lead for the Grand Challenges in Social Work on Harnessing Technology for the Social Good.  

Learning Objectives

Learning Objectives 

  • Introduction to artificial intelligence (AI) tools and their application to social work practice 
  • Articulate ethical issues of AI practices in social work 
  • Identify conditions of digital inequalities in individuals, organizations and communities.  
  • Understand the intersections of ethical AI and the NASW Code of Ethics 


Bibliography & References


Asakura, K., Occhiuto, K., Todd, S., Leithead, C. & Clapperton, R. (2020) A call to action on Artificial Intelligence and Social Work Education: Lessons learned from a simulation project using Natural Language Processing. Journal of Teaching in Social Work, 40(5), 501-518. DOI: 10.1080/08841233.2020.1813234 

Bencarnadio, M., & Greco, I. (2014). Smart communities: Social innovation at the service of smart cities. Journal of Land Use, Mobility and Environment, (SI), 39- 51.  

Berridge, C., & Grigorovitch, A. (2022). Algorithmic harms and digital ageism in the use of surveillance technologies in nursing homes. Frontiers in Sociology, Sec. Sociological Theory, 7.| 

Berridge, C., Zhou, Y., Lazar, A., et al. (2022). Control Maters in Elder Care Technology: Evidence and Direction for Designing It In. DIS’22. Designing Interactive Systems Conference.  

Berridge, C., Turner, N., Liu, L., Karras, S., Chen, A., Fredriksen-Goldsen, K., & Demiris, G., (2022). Advance Planning for Technology Use in Dementia Care: Development, Design, and Feasibility of a Novel Self-administered Decision- Making Tool. JMIR Aging. 10.2196/39335. 5:3. (e39335).  

Berridge C, Zhou Y, Robillard J and Kaye J. (2023). Companion robots to mitigate loneliness among older adults: Perceptions of benefit and possible deception. Frontiers in Psychology. 10.3389/fpsyg.2023.1106633. 14. 

Bihanic, D.  & Huyghe, P. (2015). Form follows practice. Empowering Users through Design, D. Bihanic (Ed.), 1-12, Springer: New York.  

Bricout. JC, Baker, P.M.A., Moon, N.W. & Sharma, B. (2021). Exploring the smart future of participation: Community, inclusivity and people with disabilities. International Journal of E-Planning Research, 10(2), 94-108. DOI: 10.4018/IJEPR.20210401.oa8  

Bricout, J.C., Greer, J., Fields, J., Xu, L., Tamplain, P., Doelling, K. & Sharma, B. (2021). The ‘humane in the loop’: Inclusive research design and policy approaches to foster capacity building assistive technologies in the COVID-19 era. Assistive Technology. doi:10.1080/10400435.2021.1930282. 

Bricout, J.C., Sharma, B., Baker, P.M.A., Behal, A., & Bolini, L. (2017). Learning futures with mixed sentience. Futures Journal, 87, 91-105 

Burgard,W., Milford, M., Corke, P., (2018). The limits and potentials of deep learning for robots. The International Journal of Robotics Research, 37(4-5) 405-420.  

Dunlop, J.M., Chechak, D., Hamby, W., & Holosko, M.J. (2021). Social Work and Technology: Using geographic information systems to leverage community development responses to hate crimes. Journal of Technology in Human Services. 

Fink, A. (2018). Bigger data, less wisdom: The need for more inclusive collective intelligence in social service provision. AI and Society, 33 (1) 61-70. 

Gillingham, P. (2019). Can Predictive Algorithms Assist Decision-Making in Social Work with Children and Families? Child Abuse Review, 28, 114–126. DOI: 10.1002/car.2547 



Goldkind, L., (2021). Social work and artificial intelligence: Into the Matrix. Social Work. Doi10.1093/sw/swab028. 

Goldkind, L., & McNutt, J.N. (2019). Vampires in the technological mist: The sharing economy, employment and the quest for economic justice and fairness in a digital future. Ethics and Social Welfare, 13(1), 51-63.    

DOI: 10.1080/17496535.2018.1512139 

Goldkind, L., & Wolf, L. (2015). A Digital Environment Approach: Four technologies that will disrupt social work practice. Social Work, 60(1), 85–87. 

Greer, J.A., Bricout, J., Xu, L., Fields, N.L., Tamplain, P., Palaniyandi, G., & Doelling, K.L. (2022). Robot collaborations: Using theatre performance to engage robots and humans. Liminalities: A Journal of Performance Studies, 18(4).  

Farmer, S., Bricout, J.C., Baker, P.M.A., & Solomon, J. (2022). Personas, pandemics, and inclusive, synthetic, smart city planning. International Journal of E-Planning Research, 11(1). DOI: 10.4018/IJEPR.299545 

Fernandez-Luque, L., & Imran, M. (2018). Humanitarian health computing using artificial  intelligence and social media: A narrative literature review. International Journal of Medical Informatics, 114, 136-142. 

Hodgson, D., Goldingay, S., Boddy, J., Nipperess, S., Watts, L. (2021). Problematising Artificial Intelligence in social work education: Challenges, issues and possibilities. The British Journal of Social Work. 

James, A., & Whelan, A. (2021). ‘Ethical’ artificial intelligence in the welfare state: Discourse and discrepancy in Australian social services. Critical Social Policy, 42(1), 22-42. DOI: 10.1177.02610183320985463.  

Rice, E., Yoshioka-Maxwell, A., Petering, R., et al. (2018). Piloting the Use of Artificial Intelligence to Enhance HIV Prevention Interventions for Youth Experiencing Homelessness. Journal of the Society for Social Work and Research, 9(4). 2334- 2315/2018/0904-0004. 

Xu L, Fields NL, Greer JA, Tamplain PM, Bricout JC, Sharma B, et al. (2022). Socially assistive robotics and older family caregivers of young adults with Intellectual and Developmental Disabilities (IDD): A pilot study exploring respite, acceptance, and usefulness. PLoS ONE 17(9): e0273479.  



Course Completion & CE Information


Category I Maryland BSWE Requirement

The Office of Continuing Professional Education at the University Of Maryland School Of Social Work is authorized by the Board of Social Work Examiners in Maryland to sponsor social work continuing education programs. This workshop qualifies for {quantity} Category I Continuing Education Units for {ethics/supervision}. The Office of Continuing Professional Education is also authorized by the Maryland Board of Psychologists and the Maryland Board of Professional Counselors to sponsor Category A continuing professional education.


ASWB Approved

Course completion requirements: To earn CE credit, social workers must log in at the scheduled time, attend the entire course, and complete the online course evaluation located in your account. After the online course evaluation is completed, you are then able to download your certificate. Partial Credit will not be given for participants who arrive late or leave early.


Unversity of Maryland School of Social Work, Office of Continuing Professional Education, provider #1611, is approved to offer social work continuing education by the Association of Social Work Boards (ASWB) Approved Continuing Education (ACE) program. Organizations, not individual courses, are approved as ACE providers. State and provincial regulatory boards have the final authority to determine whether an individual course may be accepted for continuing education credit. UMSSW Office of CPE maintains responsibility for this course. ACE provider approval period: 02/11/2021 to 02/11/2024. Social workers participating in this course receive {quantity} continuing education {ethics/supervision} credits.


Please refer to the tab "Live Interactive Webinar Policies & FAQs" for UMSSW Office of CPE policies regarding all live interactive webinar related matters.

Late Fees and Refunds

Fee & Registration:

Cost is $15 and includes CE credit.

No refunds will be granted for this course


Target Audience

Social Workers, LCPCs, and Psychologists

All those interested in Topic Welcomed

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