Human-AI Collaboration: Imperative to strike the right balance between futurising and humanising

Understanding Human-Gen AI Collaboration

Human-gen AI collaboration refers to the synergy between human intellect and generative AI, resulting in a partnership in which one complements the other's capabilities. In this collaboration, humans supply context, empathy, and ethical judgement, while AI provides huge data processing skills, pattern recognition and predictive analytics. The development and use of AI systems should incorporate human characteristics from the start, ensuring that the technology promotes human-centric results.

Key Considerations for Developing Gen AI Models

While generative AI has enormous potential, like with any other evolving sophisticated technological system, there are several things engineers should be mindful of when putting it to use or creating generative AI-based systems. Here’s a look at some of them:

Bias and Equality

Generative AI algorithms learn from existing data, which may unwittingly include biases from the training data. If the training data includes discriminating patterns, the generative AI models may provide biased results. Hence, it is critical for engineers to thoroughly curate and assess training data to reduce bias and ensure fairness in created content.

Data Security and Privacy

Gen AI models may require access to sensitive or confidential data during training. Data security and privacy should therefore be given top priority, and appropriate safeguards must be put in place to secure sensitive data. Additionally, data encryption and access restriction techniques can be used by engineers to prevent illegal access or exploitation of sensitive data.

Lack of Transparency

Various Gen AI models, especially large deep-learning systems, can be difficult to understand. Additionally, comprehending how and why a model produces a specific result might be tough. Thus, engineers should aim for transparency by using techniques like explainable AI, model visualisation and interpretability methodologies to obtain insights into the model's decision-making process and build confidence.

Use Cases of Human-AI Collaboration

According to Statista, the Gen AI market is projected to reach USD 6.28 billion by 2030, considering the advancements in machine learning algorithms and deep learning. Likewise, the human-AI collaboration will increase and benefit multiple sectors. Let’s uncover some of the industries that are presently benefiting from this technology and human association:

Fintech- AI excels in processing massive amounts of data at unprecedented speeds and precision in the fintech industry. This complements certain human skills, including leadership and critical decision-making. However, engineers must focus on building financial systems that involve human interactions to enhance customer experiences. In addition, human-gen AI collaboration helps in increasing production, transforming the financial landscape. Considering this, Gartner conducted a survey in which it was found that 80 percent of executives in the financial sector believe that human-AI collaboration can deliver the best results.

Human Resources- In the present time, Gen AI is helping HR departments automate tasks like creating new job ads based on skill profiles, keywords, or previous postings. They are also utilising technologies to alter postings based on context and to develop personalised communication with candidates. Moving forward, engineers should concentrate on improving AI systems' capacity to enable deeper human-to-human interactions and provide more meaningful, sympathetic candidate experiences.

Health and Pharma- AI in pharma ERP systems assists in interacting with people to streamline operations, optimise production and ensure regulatory compliance. Yet, engineers need to ensure that these systems do not undermine the human-centred care that is critical for this industry. By developing AI to assist healthcare professionals rather than replace their judgement, technology may become a reliable partner in providing ethical and compassionate care.

Wrapping Up

The human-AI collaboration has transformed the way organisations perceive creativity and productivity. While AI contributes to an organisation's innovation and production, it must also promote human capacities for empathy, ethical decision-making, and creativity. Engineers, by utilising the strengths of AI and prioritising humanisation, can develop personalised models and achieve results that were previously termed impossible. With continual technological advancements and the amazing capabilities of humans, this collaboration will undoubtedly lead to a brighter, better and more prosperous future for diverse industries.

(The author is CEO, Quarks Technosoft.)

Views are personal, and do not represent the stand of this publication.