Ethical Dilemmas In AI & LLMs: How To Navigate The Path Forward

By Ankush Sabharwal

AI and LLMs have transformed lives and societies across the globe, innovating, increasing productivity, and creating new avenues of growth. But with all that gross integration into our lives, it is important to look into the ethical issues these technologies create. Engaging with these dilemmas early will help harness by using ethical means of achieving the potentials of the technology. ​

Ethical AI Adoption: A Move Forward

The rapid increase of AI is revolutionising every industry at an unprecedented rate. A McKinsey report finds that 65 per cent of organisations now use Generative AI regularly, a nearly doubling of the total from just ten months ago. This growth highlights the increasing influence of Human-Centric methods on AI development.

The evolution of domain-specific LLMs is transforming AI solutions, while also raising ethical issues. To meet this challenge, businesses are using a lifecycle-based strategy while ensuring secure, context-sensitive interactions using AI Agents and Virtual Assistants. This facilitates the development of Sovereign AI and Secure GenAI solutions. The trend is towards Accessible AI and Voice-First technologies, powered by CoPilots, AI Assistants, and conversational interfaces such as Alexa, eSevak, AskDisha, Google Assistant and more. Composite AI is also being utilised for advanced solutions. 

Prioritising ethical adoption of AI is important to maximise the potential of Conversational GenAI, ensuring a smooth and intuitive user experience. Through this, we can promote responsible development and application of AI innovations, ultimately enriching human lives through Ease of Living. This will define the future of AI, ensuring a balance between technological progress and responsible implementation.

Ethical Consideration 

With all that the AI and LLMs can do to human life, it is equally important to reckon with ethical considerations that could arise in their implementation in various areas of life. Some of them are: 

  • Data Privacy and Security: The most important thing to ensure is that AI systems treat the data responsibly. There should be strong data governance frameworks in place that protect user information and instill user trust. 
  • Bias and Fairness: AI has to keep evolving, through constant measuring and re-modelling, in order to reduce bias and promote fairness. Diversity in the data on which models are trained and in teams that build the models helps towards more just outcomes in these systems.
  • Transparency and Accountability: Proper documentation of the decision chains of AI will go a long way in ensuring transparency around its automation. Accountability mechanisms need to be in place that safeguard the AI systems from ethical transgression.
  • Intellectual Rights: An ecosystem around unsustainable creativity would have to be made with such fair remuneration models for the content used while training AI models to respect the rights of the creators.
  • Emotional health: One way to address users' emotional states is to devise user engagement through Conversational AI, Virtual Assistants, and CoPilots and provide seamless experiences without evaluating psychological misuse.

Embracing Ethical AI Across Key Industries

By making substantial impacts across several industries, domain-specific LLMs are reaping multiple benefits:​

Education: AI agents provide tailored learning experiences to meet the needs of students individually. The global AI in education market is predicted to grow by USD 2.32 billion from 2024 to 2028, signifying a growing trend toward personalised learning approaches. 

Telecommunication: More than half of telecom providers have adopted AI and automation for better customer service and operational efficiency. 

Defence: LLMs in the defence industry enable advanced threat detection, predictive maintenance, and tactical decision-making, allowing defence forces to respond more effectively to emerging threats.

News and Media: LLMs find usage in content generation, summarisation, and audience engagement that can contribute to the expected market having a size of USD 0.73 billion, growing at a CAGR of 38.2%. ​

Travel and Tourism: As of early 2024, around 40% of global consumers reportedly used AI-based tools for travel planning, which would include personalised itineraries and thereby improving the travel experience. 

Retail and E-commerce: It is predicted to reach USD 8.65 billion by 2025 as AI-powered personalised shopping and relevant management start to kick in. Listen to your customers while they shop personally with the aid of chatbots and AI agents. It has resulted in improved customer retention and sales.

Fintech, Insurance, Banking, and Payments: Data in LLMs will be used to enhance risk assessment and fraud detection by analyzing large sets of data for both purposes. It provides improved safety mechanisms and operational efficiency.

Healthcare: AI-enabled tools will assist patients and practitioners in administrative and communication-related tasks, thus allowing more focus on patient care. 

AI and LLMs in different industries offer many variables to enhance the human condition. The development of advanced models such as ChatGPT, Gemini, BharatGPT, and Llama highlights the immense potential of these technologies. By pre-emptively addressing ethical concerns, a sound foundation will be established for these technologies to emerge as positive forces in fostering innovation and guaranteeing societal advantage.

(The author is the Founder and CEO, CoRover)

Disclaimer: The opinions, beliefs, and views expressed by the various authors and forum participants on this website are personal and do not reflect the opinions, beliefs, and views of ABP Network Pvt. Ltd.

technology