Technology in SW

** Page in building **

Technology in Social Work?

Technology can play a pivotal role in the development and design of social interventions, enabling social workers to craft innovative and evidence-based solutions tailored to individual and community needs. By leveraging technology, social workers can create interventions that are more efficient, scalable, and sustainable, ultimately maximizing their impact on vulnerable populations. However, it is crucial to tread carefully, as there are potential dangers and risks associated with technology in social work. Ethical considerations, such as ensuring client data privacy and confidentiality, informed consent in digital interactions, and maintaining cultural sensitivity in virtual settings, must be paramount to avoid any violations of the code of ethics of social work. Moreover, as we explore the potential of artificial intelligence and predictive analytics, it becomes essential to ensure that these tools are used responsibly, safeguarding against any unintended biases that could perpetuate inequalities.

We do not want to “move fast and break things” (Taplin 2017) . We want to move thoughtfully and fix things. Through thoughtful research and cautious implementation, we can harness the power of technology to enhance social work practice while staying true to our social work profession core values in Singapore.

What are the key areas I am interested to explore in my research:

1) Identify key competencies to be considered for social work education and continuing education regarding technology in social work practice

2) Develop the code of social work ethics to consider standards for technology in social work practice

graph TD
  Mission --> id(6 Core values)
    id(6 Core values) --> id2(5 Ethical Principles) 

  id2(5 Ethical Principles) ==> Client
  id2(5 Ethical Principles) --> Colleagues
  id2(5 Ethical Principles) --> Practice_Settings 
  id2(5 Ethical Principles) --> Profession
  id2(5 Ethical Principles) --> Society

    Client ==> id3(5. Professional boundaries with client)
    Client --> 6.Privacy_Confidential
  Client --> 7.Client_Records

id3(5. Professional boundaries with client) ==> id4(f. Electronic Technology)
Figure 1: Electonic Technology in the Code

3) Build good science to drive the design and development of technology in social work

4) Design and develop the interventions that can harness the power of technology

Interested to work together?

I am still building this page. But help, ideas, collaborations are always welcome. I welcome students who are interested to do research in these areas for their dissertations/ISMs/summer jobs. Practitioners in social service agencies and you want to explore more? Come let’s talk over a coffee!

References

Bibbs, Tonya D., Samantha Wolfe-Taylor, Nicole Alston, Mackenzie Barron, Lillian Beaudoin, Samuel Bradley, Alexis Speck Glennon, et al. 2023. “Constructing the Future of Social Work Tech Habits of Mind With the Ethical OS.” Advances in Social Work 23 (1): 132–47. https://doi.org/10.18060/24978.
Ibrahim, Hussein, Xiaoxuan Liu, Samantha Cruz Rivera, David Moher, An-Wen Chan, Matthew R. Sydes, Melanie J. Calvert, and Alastair K. Denniston. 2021. “Reporting Guidelines for Clinical Trials of Artificial Intelligence Interventions: The SPIRIT-AI and CONSORT-AI Guidelines.” Trials 22 (1): 11. https://doi.org/10.1186/s13063-020-04951-6.
McInroy, Lauren B. 2021. “Teaching Technology Competencies: A Social Work Practice With Technology Course.” Journal of Social Work Education 57 (3): 545–56. https://doi.org/10.1080/10437797.2019.1671272.
Reamer, Frederic G. 2018. “Ethical Standards for Social Workers’ Use of Technology: Emerging Consensus.” Journal of Social Work Values and Ethics 15 (2): 7180. https://jswve.org/down load/15-2/articles15-2/71-Use-of-technology-JSWVE-15-2-2018-Fall.pdf.
Sharma, Ashish, Inna W. Lin, Adam S. Miner, David C. Atkins, and Tim Althoff. 2023. “HumanAI Collaboration Enables More Empathic Conversations in Text-Based Peer-to-Peer Mental Health Support.” Nature Machine Intelligence 5 (1): 46–57. https://doi.org/10.1038/s42256-022-00593-2.
Sharma, Ashish, Adam Miner, David Atkins, and Tim Althoff. 2020. “EMNLP 2020.” In, 52635276. Online: Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.emnlp-main.425.
Taplin, J. 2017. Move Fast and Break Things: How Facebook, Google, and Amazon Have Cornered Culture and What It Means for All of Us. Expert Thinking Series. Macmillan. https://books.google.com.sg/books?id=yqZKvgAACAAJ.