Artificial Intelligence (AI) today benefits society by providing scalable and innovative solutions worldwide. It challenges human intelligence and makes it easy to perform any function including across industries like manufacturing, production, healthcare, retail, or even automated driving. AI systems understand and read human behaviour to increase productivity and provide an enhanced consumer experience.

AI-based systems have a high potential for technological innovations in the mobility industry and created various growth opportunities. For instance, AI-based ADAS systems help in building EVs with enhanced interactive systems which enhance the driving experience.

But along with driving business avenues, these AI algorithms are also scaling up the legal, operational, and regulatory risks. In such situations building up ethical AI is an important thing to do. Governments across the world are designing and implementing AI regulations. Industry giants such as Facebook, Google, Microsoft, and even large automobile companies are developing teams to deal with ethical issues and minimize the risks associated with the use of AI tools and algorithms. 

How to build an ethical AI?

A clear protocol that identifies and mitigates the risks is designed to save any company from falling into ethical pitfalls. Building an ethical AI can be challenging for any industry.

Though there is no one-size-fits-all outlook, a few points are to be considered generally to build a transparent, safe, and ethical AI framework for the mobility and energy industries. 

Privacy control and safeguarding data: As AI algorithms function and interpret data fed to them through radars, sensors, and through driver inputs, it is vital to safeguard the information. Data patterns developed through AI systems should be kept private. Rules regarding sharing of information with insurance and other companies should be dictated to avoid bias and information leaks in any case. 

Building ethical but user-focused AI systems: Though the algorithms deal with sensitive information, it is important to develop AI systems focusing on user benefits. In addition, it is also important to build ethical AIs that do not exploit information and enhance the user experience. For instance, using smart grids built on AI algorithms can help in analysing data and making timely decisions regarding smart energy allocation, thereby mitigating the energy distribution challenges in the world.

Holding high accountability: AI-based systems have paved a way for advancements in the mobility industry. For instance, in November 2022, a mobility technology company, Maples AI, partnered with the xBridge innovation centre and announced its plan of testing remote-controlled cars at the Pittsburgh International Airport. Such applications of AI-based systems should be monitored by a dedicated group in companies. The group is accountable for the ethical implications of AI-based systems, their development, and also its misuse under any circumstances.

Being transparent: Companies should maintain high transparency regarding the overall data interpretation and usage of AI algorithms. The technological advancements in AI systems should be opaque and reflect the high risks involved, predictions, and actions taken by these AI systems. 

Safety and lawfulness associated with AI: Ethical AIs put society and humans first. Ethical AI systems, at every stage, should comply with all the laws and regulations. These are important due to the heavy dependency of AI systems on data interpretation. 

For instance, Eurelectric, the federation of the European electricity industry believes that by the year 2025, 81% of energy sector industries will have adopted AI applications for developing predictive algorithms which boost the clean energy transition.

While doing so, the Energy sector companies need to refer to AI guidelines laid down by the European Commission. These guidelines mention the human-centric and trustworthy usage of AI systems while abiding by its robust AI rules and regulations. 

Conclusion

As the world moves towards AI-based solutions, building ethical and transparent AIs will become an utmost priority. It becomes an important practice to safeguard companies from legal as well as reputational risks. Moreover, the use of AI systems in the energy and mobility space can not only overcome world problems such as high power requirements, and increasing carbon emissions but also develop a sustainable approach towards deploying AI-based systems.