Recently, AI researchers at Anthropic were able to teach their Claude AI model to do what would have been impossible just a few years ago: control mouse cursors, click buttons, and use PCs essentially like a real human. That seems like a significant threshold for the true autonomy of artificial intelligence.
However, we’re not at the point where we can leave the keys to the kingdom to AI agents and ML platforms. In many cases, we still need a human in the loop to evaluate performance and provide feedback on an AI/ML model’s predictions.
“These tools are not magic, they are still imperfect, and they still need to have a human in the loop and need to be used in the context of mature cybersecurity processes,” said Lisa Einstein, Chief AI Officer of the Cybersecurity and Infrastructure Security Agency (CISA).
Though it can be exciting to implement new AI functionality and platforms, there are certain instances when the perspectives of human experts and ethicists are needed. Here are a few examples where the input and oversight of human beings is still invaluable:
Regulatory Compliance
Meeting all the requirements facing your industry can be a daunting challenge, and generative AI can be a tempting resource to help audit processes and create compliant organizational documents. Regardless, it’s still critical to have legal and regulatory experts involved in reviews and evaluations of any AI output.
For example, healthcare payors know the difficulty of actively maintaining the comprehensive set of policies, procedures, and workforce training materials to remain compliant with HIPAA. With each new update, organizations need to reevaluate and modify their existing documentation and protocols, which can be significantly simplified with the help of AI. The risk of fines and other criminal penalties require humans in the loop to validate any tracked changes and outline the documented decision-making process.
Financial services, insurance, and automotive sectors are subject to other regulatory bodies and laws, but the principle is still the same. AI can help to identify patterns of non-compliance and automate reporting, but human experts are needed to triple check compliance and ethical considerations along the way.
Fraud Detection and Prevention
The ability of artificial intelligence to compare ostensibly unrelated data points and find new patterns has been indispensable for fraud detection. Artificial intelligence in banking, health insurance, government benefits distribution, and other use cases is raising the bar for scammers to overcome. Plus, AI fraud detection can analyze colossal amounts of data in real-time, preventing fraud early in the decision-making process.
With insurance payouts, loan approvals, or government assistance on the line, any mistakes made by artificial intelligence can have a sweeping impact on numerous individuals. A human in the loop can help organizations to encourage scrutiny in the decision-making process and avoid biases in training models that erroneously flag authentic applications and transactions.
Where do humans fit into AI fraud detection? They can contribute to regular audits as well as escalations. Human agents have the experience, depending on their field, to investigate flagged cases. They can pinpoint the differences between intentional, malicious fraud and legitimate anomalies (rare medical diseases, valid card-not-present transactions, force majeure scenarios, etc.) or misinterpretations from the AI model.
Benefit Plan Design and Administration
When it comes to designing benefits plans, most organizations are not reinventing the wheel. AI platforms can study employee data at an accelerated pace to determine a variety of benefits options that will best serve policyholders and their beneficiaries. This simplifies the selection process for HR professionals by giving these customers a tailored and pain-free experience.
Generative AI can help employees pick the ideal plan during enrollment season. AI chatbots can translate the impenetrable language of health options into comprehensible terms and answer questions. When questions arise as consumers use or prepare to use their benefits, support bots, built from large language models, can answer questions and streamline processes.
In spite of all that, human agents still play an important role in verifying the alignment of benefits packages with an organization’s needs, culture, legal requirements, and demographics. The key reason lies in the repercussions of implementing the wrong policy.
Healthcare insurance is a massive investment, and if AI chooses the wrong plan, it can result in extended consequences. A human in the loop prevents expensive waste spending and mismatched benefits.
Balancing Automation with Human Expertise
These aren’t the only AI use cases where humans can make a difference.
How do you determine when a human in the loop is essential for an AI use case? Here’s a rule of thumb. When ethical considerations, high stakes, regulatory compliance, and unpredictable scenarios are involved, human expertise provides the balance AI requires to truly thrive.
As you build a future powered by AI, keeping humans in the loop isn’t just prudent; it’s a cornerstone of a responsible and mature AI strategy.
Are you looking to find the right balance between AI tools and keeping a human in the loop? w3r Consulting can help you create an AI foundation.
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