Written by Brandon Yu I 4 min read
Key Takeaways:
- Human in the loop (HITL) is where a human interacts directly with the AI model, providing invaluable feedback that refines and enhances the model’s decision-making prowess.
- HITL mitigates risks and align the technology with ethical standards and regulations, while allowing for quicker deployments of AI solutions and helping organizations to go to market sooner without compromising on reliability and accuracy.
Generative Artificial Intelligence (GenAI) stands as a transformative force in today’s technology landscape, primarily serving to automate the simple and repetitive tasks that occupy human bandwidth. By taking on the mundane, GenAI empowers us to redirect our focus towards more creative and intellectually stimulating pursuits. It’s a breakthrough that’s redefining the boundaries of what’s possible, enhancing productivity, and driving innovation (Harvard Business Review).
However, with such powerful technology comes the imperative need for vigilance. Concerns surrounding data privacy and the regulation of AI outputs are more pronounced than ever. The potential implications of GenAI necessitate close human oversight to ensure its responsible and ethical use.
It’s crucial that human operators retain control and understanding of AI operations, to mitigate risks and align the technology with ethical standards and regulations.
That is the limitation of GenAI solutions, and that’s why it’s crucial to implement a human-in-the-loop for the foreseeable future.
A Human in the Loop improves AI Models
Human in the Loop (HITL) stands as a critical process, acting as the bridge between human intellect and AI capabilities. It is through this process that a human interacts directly with the AI model, providing invaluable feedback that refines and enhances the model’s decision-making prowess.
This interaction isn’t a one-way street; it’s a symbiotic relationship where humans guide AI towards improved functionality and, in turn, AI enables humans to focus more on complex and creative activities.
In consumer-facing models, such as customer service AI chatbots, human intervention is not just a tool for enhancement but also a safeguard. Humans step in when the model is uncertain or when a user explicitly requests human interaction, ensuring that the model’s offerings are precise, reliable, and meet the users’ needs effectively.
A critical error in current AI models: hallucinations
Through our experience building our own AI models, we’ve come across various hallucinations.
The concept of “hallucinations” in AI models refers to instances where the AI generates incorrect, distorted, or nonsensical outputs, often stemming from its misinterpretation or overinterpretation of input data. It’s a phenomenon that underscores the limitations of AI when venturing into domains demanding nuanced understanding or specialized knowledge.
This is of notable concern. Without a human in the loop, these models would be providing misleading information to its users. Let’s illustrate with a quick example.
In the realm of poker coaching, an AI might suggest strategies based on probability calculations but might miss the psychological subtleties and human behaviors that experienced coaches would consider. It may misread poker shorthand or specific notations that is common practice to an experienced poker player. We’ve been hard at work to solve those discrepancies as we build out the world’s first AI poker coach.
We see how AI excels at transforming generalists into quasi-specialists by providing insights and capabilities previously reserved for experts.
However, the nuanced intricacies and subtle inconsistencies that only a true specialist can discern remain outside its reach. This is precisely where the importance of HITL becomes paramount. It’s the discerning human eye that catches the anomalies AI might overlook and provides the nuanced feedback necessary for continual refinement and accuracy.
There are key advantages of incorporating a human in the loop
In a future landscape dominated by AI, it’s the harmonious collaboration between human insight and technological prowess that will drive the next wave of innovation and progress. Let’s recap the key advantages.
- Enhanced User Experience: HITL combines AI's speed and scalability with human intuition, ensuring users benefit from the immediacy of AI, while humans address more nuanced questions, providing more accurate and context-rich responses.
- Continuous Model Improvement: The constant interaction and feedback from humans enable the AI model to refine and enhance its data core continually, improving its decision-making capabilities and accuracy over time.
- Accelerated Market Readiness: HITL allows for quicker deployments of AI solutions, helping organizations to go to market sooner without compromising on reliability and accuracy.
- Management of Ethical and Social Implications: The integration of human input helps in navigating and managing the complex ethical and social considerations associated with AI, ensuring responsible and ethically sound applications.
- Error Reduction: Human oversight acts as a corrective layer to the AI’s outputs, identifying and rectifying errors and inconsistencies, thereby improving the reliability and trustworthiness of AI solutions.
A great example of HITL is through Keeper Tax’s AI Accountant. This AI accountant has ingested US federal and state tax legislation. Each answer will receive a human tax professional’s review, which factors into a percentage accuracy of how accurate the answers are.
This gets correct answers quickly to the hands of their users, with the quality assurance that builds trust within their existing customer base.
The necessity to apply a human in the loop to your AI model
It's imperative for companies to proactively integrate human supervision over their AI models, embracing the HITL approach. This strategy allows organizations to harness the expansive capabilities of AI efficiently, without the extensive capital investment typically associated with assembling comprehensive datasets required for going to market.
We’ll quickly see this as a common theme in customer service chatbots, like RachelAI, as well as various AI coaches across industries.
By leveraging HITL, companies can swiftly and responsibly ride the AI wave, ensuring a seamless fusion of technological prowess and human insight.
This balanced interplay not only optimizes the potential and reliability of AI solutions but also fortifies them with the invaluable subtlety and discernment inherent to human cognition, paving the way for a future where AI is not just smart but also wisely calibrated.
