The evolution of inclusive AI: breaking the resistance through technology

The transition of Artificial Intelligence (AI) from a future technology to an ongoing trend is remarkable. AI is reshaping industries, public sectors, and society with its transformative capabilities. Every domain we can think of is using or can use AI. The promise of building a sustainable yet efficient future can only work if the development and applications of AI are inclusive. Despite AI’s unparalleled efficiency, creativity and intelligence, there are a multifold of technical, ethical and cultural barriers which exist that need to be confronted.

As we stand on the brink of a future driven by AI, it is paramount to address how we can leverage and implement it to include AI across all domains, regardless of demographic, geographic, or socioeconomic factors.

What is Inclusive AI?

Inclusive AI is the art and science of incorporating AI features that are accessible and beneficial to people of all backgrounds. It focuses on using AI technologies in different verticals for diverse people regardless of race, gender, socioeconomic background, or ability. Considering the needs, experiences, and perspectives of a wide demographic of people in a diverse domain.

Accessibility: Inclusive AI focuses on making AI-powered solutions affordable for people from diverse backgrounds and remote parts of the globe.

Data representation: Inclusive AI involves raining AI models on diverse datasets to help minimise algorithmic biases, broadening data’s representation.

Accountability: Implementing the audit and rectifying mechanisms to hold unintended outcomes or discriminations to accountability further drives AI’s inclusivity.

Role of Inclusive AI across Various Sectors

With the evolution of AI, the world is heading towards a more AI-inclusive vertical where AI is helping almost every sector, such as agriculture, healthcare, manufacturing, or public services. AI transforms by enabling efficiency, scalability, automation, and innovation. In this section, we will delve into the inclusiveness of AI across various domains.

Healthcare: Through AI, hospitals systems have improved diagnostics, reducing human error, helping doctors provide personalised treatment and operational efficiency. In medical imaging, AI can catch anomalies in MRIs, X-rays, and CT scans with high precision. AI virtual assistants and robot surgeons performing remote operations are some of the breakthroughs the healthcare systems are witnessing through AI.

Manufacturing: Through AI, enterprises and industries can optimise production processes by helping ensure equipment reliability and enhanced quality control. AI also enables predictive maintenance that uses data analytics to anticipate potential wear and tear in various infrastructures, by helping address problems in advance, operational downtimes can be minimised. Quality control systems within the industry use computer vision to identify product defects during manufacturing. Robotic Process Automation (RPA) is another branch of AI and robotics to streamline repetitive tasks, helping supply chain optimisation by predicting demand and improving logistics.

Agriculture: Another area where inclusive AI is helping to revolutionise is the agri-sector, as AI can benefit the industry by optimising farming practices and improving yields. Precision agri practices have become a well-known practice where the agriculture industries' analysts leverage AI to monitor crop growth, soil health, pest control, and weather patterns. Based on those analyses, they ensure that the farmers can better utilise resources. Smart agriculture also uses automated drones to capture real-time data on large-scale operations.

Finance: Like other sectors, the finance industry is also experiencing a massive ripple with the advent of AI. Customer services have become automated through generative AI as AI chatbots are offering personalised financial advice while handling customer inquiries efficiently. As transaction security accuracy strengthens, financial institutions using AI and ML-powered algorithms can further identify anomalies and cyber attacks, enabling higher-frequency market transactions. Improved fraud detection precision is also helping to reduce false positives occurrences.

Logistics: AI is also used in logistics to optimise fleet management and supply chains, as well as dynamic pricing and adjusting delivery costs based on demand. Through AI-powered systems and algorithms, logistic firms can plan efficient delivery routes. Automated systems and robotic process automation (RPA) can help in warehouse automation and can help track product checklists and streamline order fulfilment processes for quicker deliveries. Such efficiency can help in enhancing overall customer experience.

Technological enablers of Inclusive AI

Technology is shaping today's modern business and multiplesectors. The use of AI across all domains is backed by various technological advancements and innovations. Let us understand what technologies and concepts AI should use to become inclusive across different verticals.

ML and DL in multimodal systems: Machine Learning (ML) and Deep Learning (DL) are branches of AI that help comprehend, adjust to, and cater to diverse human needs (with personalisation), promoting accessibility. The multilingual model in applications like Google Translate uses Deep Learning (DL) and Natural Language Processing (NLP). They help enable businesses to deliver services accessible to non-native speakers and marginalised linguistic groups.

Bias reduction for better inclusiveness: AI models rely on datasets used in training AI models therefore by creating biasness through training, the number of beneficiaries of AI technology will narrow down. Consequently, to boost the use of AI across various domains, benefitting countless users, enterprises are using AI to identify and fix bias in datasets. Algorithms can detect patterns of discrimination, ensuring adequate decision-making across diverse demographics.

Enabling more accessibility: Accessibility is the key to taking AI to the masses, requiring different aids. By utilising Machine Learning models, enterprises can deliver fundamental support for accessing various AI solutions through speech-to-text applications, helping individuals with hearing impairments. Advancements in AI sub-domains like Computer Vision (CV) and real-time object recognition can also help blind people portray their surroundings more accurately.

Democratisation of AI tools: Cloud-based platforms like Amazon Web Service (AWS), Microsoft Asure, and Google Cloud are also enablers - driving AI tools to reach millions of users. Cloud helps democratise the accessibility of AI solutions, empowering startups, nonprofits, and small businesses to use computational power on demand. From storing tremendous amounts of data or renting computational power to scaling the AI-powered product to millions, the cloud is backing everything for your business.

The power of Explainable AI (XAI): Explainable AI (XAI) is another significant concept that is essential in developing inclusive AI systems. It ensures fairness, trust, and transparency in various autonomous decision-making processes. By enabling humans to comprehend, interpret, and validate AI outputs, XAI contributes to the development of AI systems that are equitable, accountable, and accessible to a wide range of people globally.

The Future of Inclusive AI

Leveraging AI in various fields for a diverse array of people is an ongoing journey. Inclusive AI is not merely an ethical compulsion but a necessity where the whole nation can use AI across various verticals. With the merging of emerging technologies like quantum computing and advanced natural language processing, inclusive AI promises to deliver greater inclusivity. Collaboration between private and government sectors can play a notable role in fostering innovations in every domain we can imagine. By integrating blockchain technology with AI, the public and private sectors can also deliver cutting-edge solutions to the citizens, promoting better integrity and security to AI-powered solutions.

Inclusive AI, with the help of machine learning, natural language processing, computer vision, IoT, and the cloud, can evolve to create a more connected, equitable, and prosperous world. To know more visit VE3 or contact us directly.

techUK’s TechTogether campaign, taking place throughout March, is a collection of activities highlighting the UK’s technology sector pursuit to shape a more equitable future. In 2025 we are exploring: Inclusive AI, investing in diverse founders and entrepreneurs, the power of allyship and mentorship, and empowering young people.