Many companies are turning towards automation, using artificial intelligence, big data analytics, deep learning, and cognitive machine learning to improve efficiency. However, these technologies may not be able to perform complex tasks or make decisions on their own. Humans and machines go hand in hand, the future of technology with human-in-the-loop is inevitable. A fact reiterated by Gartner’s prediction“By 2025, 30% of new legal technology automation solutions will combine software with staffing for a “human-in-the-loop” offerings.

The State of Human in the Loop in Legal

Human-in-the-loop machine learning does not hinder total automation. Instead, it combines the value of human cognition with the constantly evolving technology of artificial intelligence, making it more effective and realistic. Human expertise is critical in helping technology progress toward full autonomy.

The major reason for the technology adoption not being true aid for the legal industry is the incoherence between the two. That is, the machine is not trained well to do what it takes for legal industry professionals to accomplish complete automation. The involvement of human expertise in fine-tuning the tools and algorithms is essential for accelerating the adoption of automation and making it a reality.

Evolving with an expert

Well, humans and machines go hand in hand in every step of the world process. Human-in-the-loop is the primary concept to be embraced. To move a step further, human-in-the-loop combines the efforts of human expertise and cognitive machine learning to build more ingenious solutions. It aims to develop an extended team to achieve what humans and machines cannot achieve individually. This reality holds true with every AI tool being built, including the sensational ChatGPT. In this article on OpenAI, the developer of ChatGPT, you will find the mention of learning through human feedback. That simply says the involvement of humans in building AI to augment human efficiency.

The key to smart and true digitization

Arguing total automation to be game-changing indicates a complete dependency on an AI system to perform cognitive functions that are deemed suitable. Humans in the loop act as a bridge between the system and its end-users. This bridge performs the essential task of diligently guiding the system to make absolutely ‘correct’ decisions and aids transparency through processes.

The key takeaways from HITL are:

  • Accuracy: Automated solutions can develop human-level precision, consistency, and high accuracy with training and feedback learning patterns.
  • Rare data augmentation: HITL will aid in identifying patterns from unlabelled and rare data to develop a human-aided cognitive recognition and further learn from the structure devised.
  • Efficiency: HITL enables a rigorous and highly productive workforce that uses cognitive data to learn from humans and perform better.
  • Safety: Feedback-led training enables humans to monitor what the machines are doing. This builds a structure of highly safe operations and data handling.

HITL helps the software or system to evolve with the change in objectives gradually. Through rigorous human training and interactions, any AI system develops the capacity to break through dilemmas and perform confidently correct actions.

Machine learning or human teaching?

AI machines, including the ones for the legal industry, continue to learn as human keeps teaching.
It is time to understand the absolute need for human expertise and intelligent quotient combined with technology to conquer the perfect digital solution.

Human-in-the-loop creates an architect of learning models for the machines that are to be regulated by constant human feedback. When an engine fails to identify the data, humans must intervene to aid the solution. Thus, human employability in the form of data handler and labeler takes a step ahead.

In the legal space, it will be required to adopt an AI-enabled Contract Lifecycle Management (CLM) solution. For instance, it indeed takes deep expertise to be involved in training the AI system in tune with specific needs.

The primary aspects that come into play while dealing with HITL are:

SMEs: Subject matter experts work closely with human-in-the-loop solutions to create a chain of feedback-enabled training. Legal experts use their collective knowledge gained from research, academics, and experience to create a training set, feed it to the machines, and get it accustomed to intended processes/tasks.

Workforce: With the world pushing towards automation, companies are cutting down on human headcounts. While it is evident that AI potentially pacifies productivity, the need for a workforce is valid to build the perfect solutions to prevailing business needs in a legal department.

Try out Cenza’s legal service effective HITL

There are various ways to avail human-in-the-loop solutions in your legal firm setup. While the thought might seem daring, it is nothing but a step towards incredible perfection achieved through automation.

Cenza’s human-in-the-loop machine learning solutions are designed to streamline the complex AI learning process and get the tool up and ready to be your legal tech partner.

To explore how our AI/ML training solutions can make a difference in accelerating the digitization process, talk to our experts today. It will give you a new perspective on human-in-the-loop as a solution.


About the Author: Jayashree Nair

Jayashree has managed various engagements at Cenza for clients across the world. She led scoping and solution development for more than 20 client engagements, including some complex contract management-related requirements for clients and works on a daily basis with Ironclad and their clients on contract migration projects. She has successfully transitioned many complex projects for a variety of clients in the managed legal, AI and ML training, and Contract management space. She has an overall 12 years of experience, including previous stints at Accenture and R.R. Donnelly and has a strong understanding of project management and contract management projects.