By clicking “Accept”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.
September 29, 2023

Enhancing Generative AI with Human in the Loop: the beginning of an unlimited collaboration

September 29, 2023

I. Introduction: Enhanced Humans and Generative AI – A win-win Collaboration

At isahit, we often refer to our workforce as "enhanced" by Generative AI, where the individuals collaborating with us are "Augmented Humans" consistently delivering near-perfect quality in all their digital tasks.

However, it's essential to acknowledge that they also play a crucial role in supporting Generative AI tools, whether it's through training AI models or participating in a human-in-the-loop system.

Generative AI has gained significant attention in recent months, unquestionably emerging as a game-changing technology across various industries. We are undeniably witnessing the early stages of this AI revolution.

Generative AI has a plethora of capabilities, from generating texts and images to effectively classifying, extracting, and tagging content. All technological tools incorporating Generative AI significantly enhance the speed and efficiency of content creation and modification made by humans. Currently facing to this solid and promising revolution, at isahit, we recognize that our core business is deeply evolving.

Nevertheless, we strongly believe that humans will continue to play a crucial role in the Generative AI production process. What we call the Human-in-the-Loop in our Data Labeling/Processing industry. Humans possess unique qualities, including precision, contextual understanding, judgment, creativity, and background knowledge, which machines cannot fully replace but rather complement and enhance... The key lies in strategically integrating Generative AI into our daily operations, leveraging its potential to assist us in producing relevant content, developing outstanding products, and making informed decisions.

Generative AI, much like jurisprudence, is an evolving discipline. Drawing from the past as a foundation, it embraces the present as a new perspective and anticipates the future as an ongoing process of correction and adaptation.

II. The recent evolution of Generative AI capabilities

In recent years, Generative AI, a part of Learning Management System (LLMS) technology, has made significant strides, becoming proficient in generating content across a wide array of domains. A decade ago, it was primarily text generation that saw advancements, with a limited connection to the realm of robotics. Today, however, Generative AI has killed these boundaries, demonstrating remarkable precision and quality in generating images and videos, marking a visible expansion in its capabilities. This technology can easily switch between different types of formats, and as more people use it, it's expected to become even better, creating even better content in the future.

Moreover, Generative AI, which previously focused on few knowledge domains, has evolved to generate content and provide information across a multitude of subjects. This ensures that all industries can benefit from the potential of Generative AI, always remembering of the indispensable role of humans in ensuring security and maintaining content quality.

This evolution recalls the growing necessity for humans to be involved in Generative AI training to continually enhance its capabilities. Training Generative AI models for tasks such as text classification is relatively straightforward, but challenges arise when tackling complex subjects like medical image analysis, such as brain scans.

As Generative AI keeps evolving, the demand for highly skilled and specialized labellers is expected to grow significantly.

III. Detailing the place of Human in the Loop in Generative AI Workflows.

In the rapidly evolving world of artificial intelligence, one thing is clear: the synergy between humans and machines is necessary to reach the full potential of Generative AI.

The best of AI : Speed, combined with the best of Humans : Expertise.

Generative AI has the capacity to generate content and code at a pace that seems almost supernatural for human-being. However, it is compromised, and subject to errors, inconsistencies, and biases. This is where the eye of humans becomes necessary. Ilya Sutskever, OpenAI's chief scientist, acknowledges that AI models will continue to evolve, but the human touch remains irreplaceable. It's the fusion of AI's computational process with human decision-making, ethical judgment, and critical choices that elevates the quality of AI-generated content.

Human-in-the-loop and Generative AI: the back and forth of Feedbacks and Improvements.

Human-in-the-loop isn't a one-time interaction; it's an ongoing, iterative process between the annotators and the content annotated automatically. Basically; Human-in-the-loop involves human experts in the training and adjustments of AI systems. Humans meticulously data (preprocessed by GenAI for instance), cleansing it of inconsistencies, cleaning errors and biases. In order to create high-quality training data for future models. They actively participate in the training of AI models, interact with them for refinement and optimization.

Three types of Human involvement: HITL, HIC and HOTL.

To understand the spectrum of human involvement in training of AI, we can divide their position in the workflow in three approaches:

  1. Human-in-the-Loop (HITL): In this approach, humans are engaged in the decision-making and learning process of the machine. AI makes decisions, but the results are controlled by a labeler who can correct if necessary. This ensures that AI continues to learn and improve under human(s) supervision.
  2. Human-on-the-Loop (HOTL): HOTL leans more towards automation. AI makes decisions autonomously but seeks human intervention periodically when unexpected situations arise. Data Labelers step in to resolve exceptional cases rather than continuous control over the outputs.
  3. Human-in-Command (HIC): In this approach, humans have the final words. AI provides suggestions and recommendations, but it's humans who make the ultimate decisions and have control over final actions taken. AI acts as a decision-support tool but cannot act autonomously without human validation.

In essence, HITL, HOTL, and HIC exemplify the spectrum of collaboration between humans and AI, each with its unique advantages and applications. As we navigate the intricate landscape of Generative AI, it becomes evident that the real magic lies not in the machine alone but in the symphony of human expertise guiding it towards excellence. With HITL as our compass, we embark on a journey where AI continues to learn, adapt, and improve, hand in hand with the guardians of wisdom—humankind.

IV. Human in the Loop and Generative AI: Examples and Benefits

Real-world examples show us how the remarkable impact of Human in the Loop can leverage the content quality produced by GenAI tools

  1. CoPilot's Coding Brilliance: In the coding world, Generative AI assistants like GitHub's CoPilot and Amazon's CodeWhisperer collaborate effectively with Developers, resulting in increased efficiency and clean code. Microsoft's integration of CoPilot into Microsoft 365, despite added costs, demonstrates how Humans are ready to deal with such technologies.
  2. AI-Powered Analysis in Healthcare: AI (in pre-labelling or building from scratch Medical images, assists surgeons, enhancing surgical procedures and reducing errors.

The Advantage of Human-in-the-Loop

Here are some key benefits of Human-in-the-loop added in “development” of AI models.

  • Enhanced Content Quality: Humans are the assurance of quality. The result is automatically generated content adapted with creativity but also on a coherent, relevant, and accurate basis.
  • Contextual Adjustments: Humans help AI tools producing content by adding the nuances of human understanding and context. This ensures that the content not only makes sense but has a fit to its intended audience.

At isahit, we stand at the forefront of this fast-moving revolution, building tools and workflows to get the most of Human-in-the-loop and Generative AI combined. The goal being to craft content that not only meet expectations, but a content that grab the best from robots and humans.

VI. HITL + Generative AI: Ethical challenges and future concerns.

When discussing "Human in the Loop" interaction with generative AI tools, some challenges come to the forefront. For example, implementing "Human in the Loop" can be complex, with scalability and cost emerging as major concerns. This is why, at isahit, we assist companies in constructing smart workflows and integrating the right workforce to maximize the benefits of these workflows.

Furthermore, the ethical dimension remains substantial as we manage human feedbacks, peristently working to identify and rectify potential biases while looking for the best relevance.

In our journey towards AI improvement, it is essential to underline the importance of responsible AI development and effective regulation, whether by companies or governments. These pillars ensure that the AI revolution aligns harmoniously with our values, guaranteeing that in our future, innovation coexists with ethics and integrity.

The future is full of possibilities when talking about the collaboration between AI and people. AI, with the guidance of human interactions, will learn and adapt at an unprecedented pace. The synergy between human expertise and AI algorithms holds the promise of generating more advanced and creative AI systems in the next decade.

While true autonomy in AI models may be a realistic in a near future, recent outputs generated by AI and demonstrate that the role of human is significant in producing a qualitative content. Despite concerns about job replacement, Generative AI is a work in progress, demanding human collaboration to reach its full potential.

As we look forward, the relationship between Labelers and Generative AI in content generation is a infinite one, and the journey is just beginning.

You might also like
this new related posts

Want to scale up your data labeling projects
and do it ethically? 

We have a wide range of solutions and tools that will help you train your algorithms. Click below to learn more!