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The Critical Importance of Validation in Social Work AI







The Social Work Magic Suite of AI tools was created to alleviate some of the burdens social workers face, making their tasks more manageable and less stressful. As we utilize this technology to help us take control of our workflow, we must ensure that we use it responsibly. The video above focuses on an aspect of social work AI that remains critically important as AI becomes more integrated into our field: the necessity to validate AI-generated results.


The Reality of AI Errors

Recently, it was reported that some bizarre responses had been produced by a new AI model from Google. These included absurd suggestions like eating rocks and adding glue to pizza sauce—clearly, not reliable advice. Although these examples are extreme, they highlight an important point: AI can and does make mistakes.


As you may already know, I have developed the "Six Pillars of Practical and Responsible AI Use for Social Workers", which many Social Workers now use to help them navigate through this new and exciting technology. Almost by definition, every one of the 6 Pillars is important, but the argument can be made that this one is the most vital to practicing responsibly with AI.


The third pillar of responsible AI use in social work is to always validate your results.


While AI tools can be incredibly powerful, they are not infallible. As Social Workers, our work often involves critical and sensitive issues, where the accuracy of the information that we use is vital to the work that we do. Therefore, it is essential to thoroughly review any AI-generated information before using it as a basis for any decision making, using it in documentation, reporting, etc.


AI and Validation: A Necessary Practice

Validating AI outputs means more than just a quick glance. It involves critically assessing the information for accuracy, relevance, and cultural appropriateness. For instance, AI could theoretically generate results that are biased against certain individuals or groups of people, or contain subtle errors in grammar or context. It is our responsibility and ethical obligation to catch these mistakes and make corrections as needed.


Additionally, we need to ensure that AI-generated responses align with the specific needs of our clients and the populations that we serve, as well as the ethical obligations of our profession. This means that when using AI, we must always check for things like bias, inaccuracies, or culturally inappropriate content. If the AI output does not meet our standards or produces responses that are not true or relevant, it is up to us to correct and and modify responses before we use them in the real world.


The Third Pillar of Responsible AI Use

For all of the reasons above (and more) we must continuously keep the third pillar of responsible AI use at the forefront: validation. We must remember that while AI can significantly streamline our work and save us time, it is not a substitute for our professional judgment and ethical responsibilities. By validating AI results, we ensure that the information we provide is accurate and trustworthy, thereby maintaining the integrity of our work.

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