Keeping Artificial Intelligence Accountable to Humans

AI and its constituents like machine learning (ML), deep learning (DL), augmented reality (AR), virtual reality (VR) and predictive analytics have created a buzz in recent times with widespread adoption. However, even with the very best of technology from an Artificial intelligence services provider in USA reliant on computer algorithms, initial programming and software design to take actions, questions on ethics and accountability are still going to arise.

Today, the growth in AI usage is phenomenal and undoubtedly driving several business and industrial sectors. AI is almost embedded into all basic and major applications in everyday life. With the use of algorithms in AI to track, study and monitor basic to complex data patterns, decision making has made huge strides based on AI-powered machines.

AI Global Statistics on Usage, Growth and Expansion

According to the latest global data trends, cognitive computing and AI systems are expected to exceed 58 billion US dollars in 2021.

Additionally, the AI industry is the fastest-growing segment in current global tech innovation attracting investment across all industries. The predicted global revenue estimates for the AI industry is expected to rise above 120 billion US dollars annually by 2025.

The cumulative year on year estimated AI market by 2025 will grow into a 200 billion dollar industry.  

AI market will grow to accumulate a global share and presence which is expected to add 16 trillion US dollars to the global economy by 2030.      

AI is one of the fastest-growing data-driven innovations globally. AI is widely adapted in healthcare systems, caregiving, business decisions, construction, traffic management, financial planning, visualisation, strategic planning both for businesses and industries, even in some aspects of criminal justice systems. 

Computer algorithms are reliant on makings logical conclusions or summations after studying submitted data patterns with software. Even though still a huge grey area, yet lack of precise accountability brings up a necessary debate. There have been cases of a data breach, exposure or leakage and users or businesses have had to face consequences. Yet in the case of healthcare what happens if the wrong diagnosis leads to a fatal or wrong outcome especially as AI is highly integrated into medical care systems? As these and more questions arise, in case of any shortfall, bias or inconsistency who is accountable? How can AI be made more accountable to humans? What strategic and ethical demands can help make AI accountable?

Strategic and Ethical Requirements to Make AI Accountable

1. Privacy for any individual or corporate is indispensable. Privacy laws have been adopted to keep in check the possibility of misuse or misrepresentation.

Personal, corporate or public data is used by algorithms to arrive at specific conclusions. The development of big data was a step to processing massive data formats in time. The institution of stricter and stringent privacy laws and standard acceptable rules for using this data brings an element of safety for users and the ability to checking AI systems. 

2. All decisions come with responsibility at all levels. It’s good to know the liability or responsibility part of software designs put out in the marketplace. This is because data formats or tools adopted vary and there may be less control over the same as users may adapt data variably with a different outcome. So standard rules of engagement must be clearly stated for all software adopted and used variably by all different users.

3. Mandate compulsory and regular evaluation or update of AI algorithms with transparent mechanisms to keep compliance with established laws and ethical requirements. Ethics is all about fairness and honesty in operations without compromise to anyone’s rights. Algorithmic bias is often spoken about without knowing how the algorithms approach a certain conclusion. That’s why their evaluation and consistent follow-up is necessary.  

4. It is best to require the maintenance of extensive records of development and design processes as well as critical decision making. With an established routine of records in design and development processes, the path to motivating and inspiring best practices and decision making is born. The reality for accountability gets traction and possibility.    

5. AI solutions providers should build systems and solutions in compliance with global and local laws. When there is compliance at the local levels it easier to track the source. However with AI transcending there is also the need to comply and adhere to all international set policies and guidelines. There are several resources to access various national and regional or geographical regulations and guidelines regarding technology innovations systems.   

Summary

Despite some limitations, AI still has several positives. There is no doubt that AI with all the allied automation and Artificial Intelligence Services have made huge contributions to human life. And AI will continue to redefine and improve businesses and industrial sectors in the coming years ahead with better and refined mechanisms for operation and usage.