Technology in SW

** Page in building **

Move thoughtfully and fix things

Technology can play a pivotal role in social work not just as productivity hacks, but also in social work practice. However, it is crucial to tread carefully, as there are potential dangers and risks. 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.

Key Areas of Inquiry

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

Identify key competencies

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

  • Social work competencies include “core knowledge, values, and skills in working .. in an area of particular practice … [as well as] competence from one situation to another irrespective of case, need, problem, or context” (as cited by McInroy 2021, 546)

  • McInroy (2021) identified five competencies of using ICT which can still be relevant to current tech:

    1. Continuing engagement with technologies
    2. Online professionalism
    3. Assessing risks and opportunities
    4. Applying professional ethics
    5. Thoughtful integration of technology into practice contexts
  • Other competencies need to be considered in the age of gen AI:

    • Data literacy and Computational reasoning. If we encourage workers to apply computational tools to solve complex problems or improve social work processes, we also need to help them develop the “ability to critically self-evaluate the way they apply these tools, and thus be able to reason effectively in a variety of contexts”.

    • Interdisciplinary tech collaborations (Storer et al. 2023)

    • In Long and Magerko (2020), which of these 16 competencies of AI are relevant to social work? . I think these competencies can be prioritized.

Social work has an obligation to enter into the discourse of AI-enhanced-everything to insert our ethical perspective into the development of algorithmic tools and products. To effectively enter the conversation, social work students need realtime examples, experience, and practice to acquire the expertise required to engage with computer engineers, data scientists, and other disciplines wrestling with the opportunities and challenges of AI. Social work must reckon with a technologically evolved human ecosystem, confronting the implications of interaction with embodied algorithms, cultivating the ability to evaluate data sources, and expanding the notion of collaboration to include the inevitability of working alongside algorithmic actors including chatbots and other digitally enhanced tools. We may need to expand our primary notions of both “person” and “environment,” working toward authentic and informed engagement with augmented and virtual realities and entering into dialogue with computer agents, including algorithms and robots. (Goldkind 2021)

Standards for Using Technology and AI in Social Work

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

  • The code of Professional ethics for social work profession in Singapore, 3rd revision (here) placed “Electronic Technology” Figure 1 in “Professional boundaries with clients” within section “A. Social Workers’ Ethical Responsibility to clients”.
  • This is appropriate considering the centrality of the practitioner-client relationship within the core value “Importance of Human Relationships” in the social work profession (Core value 6 “Importance of Human Relationships” in the SG Code; see also Reamer (2018)).
  • The ways in which social workers use technology in social work have created new ways to interact and communicate with client. This in turn has bring into focus questions about the social work-client relationship.
  • In addition, technology also has change various fronts of our profession that do not involve direct interactions with client, including the design and delivery of services, management of data, agency processes, how social workers’ relate with colleagues and supervisors, and promoting of services.
    • Social workers who use technology to provide supervision. Do these tools meet the learning need of the supervisees?
    • SSAs maintain websites and social media accounts that provide information to the public. Are there steps to ensure that the information is accurate, up-to-date, and valid? Are there propoer acknowledgements of the information or work of others?
    • Social workers increasingly use technology to communicate with colleagues either to get information for service referrals, or to understand colleagues’ practices and policies. Do we check if the info is accurate? Do we acknowledge the work and contributions made by other colleagues? Can we use technology to search personal information about colleagues?
    • How do we evaluate technology (e.g., predictive risk models)? What are the metrics we should use to evaluate the system? AI-in-the-loop feedback systems can be use to support social workers’ skills (e.g., Sharma et al. (2023)), how do we check if these systems are useful?
  • Thinking deeper about technology and our ethical responsibilities to clients as well as towards colleagues, practice, profession, and society can help us be in a clearer position in our use of technology.
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

Develop the science

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

  • Applications build on LLMs are exciting and many of these could be potentially useful for social work practice. However, some apps are not built with strong theoretical conceptualization and evidence from existing social science research.

  • Developing apps for use in social work require skills from computing, AI, or design-thinking. But they also need social science. In social science, we emphasize measurements, causal thinking, rigour models, and theories.

  • If we want to build an AI tool to support social workers’ engagement skills, we need to tap on what we know about social work engagement. Building the science is key to developing effective apps.

Develop the tools

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

  • One crucial question is how do we evaluate AI interventions? Work in this area, mostly with healthcare interventions, have found inadequate information reported by trials and missing critical information (e.g., what version of the algorithm was used? how were the training/test data selected? what was the interactions between AI and human?). See Ibrahim et al. (2021).

  • Process and outcome evaluation are crucial in understanding the effects of using these interventions. Bibbs et al. (2023) highlighted the need for social work users of technology to “engage in continuous and rapid ethical monitoring” as well as “..duty bound to proactively consider unintended consequences”(p. 141).

Interested to work together?

I am still building this page.

Projects I am working on this year:

  • Survey of Tech/AI in social service sector
  • Development of AI in text-base counseling/engagement
  • COP for tech use in social service sector?

But I am just one person. 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? We can talk over a coffee!


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.
Goldkind, Lauri. 2021. “Social Work and Artificial Intelligence: Into the Matrix.” Social Work 66 (4): 372–74.
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.
Long, Duri, and Brian Magerko. 2020. “CHI ’20: CHI Conference on Human Factors in Computing Systems.” In, 1–16. Honolulu HI USA: ACM.
McInroy, Lauren B. 2021. “Teaching Technology Competencies: A Social Work Practice With Technology Course.” Journal of Social Work Education 57 (3): 545–56.
Reamer, Frederic G. 2018. “Ethical Standards for Social Workers’ Use of Technology: Emerging Consensus.” Journal of Social Work Values and Ethics 15 (2): 7180. 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.
Storer, Heather L., Carol F. Scott, Melissa Eggleston, Toby Shulruff, and Maria Y. Rodriguez. 2023. “Reimagining Social Works Digital Future: The Critical Role of Interdisciplinary Tech Partnerships.” Journal of Social Work Education 59 (sup1): 9.
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.