Why do we need Regulations on AI!

Regulations in AI is the need of the Hour!

We?live in the world in which AI is ever-present, and ?that passively influences the simplest of decisions in our daily life. Think about it. You wake up and opens the phone with a face ID/ analysed by AI, your route to work is likely influenced by traffic and weather information provided by AI, and you might wind down in the evening, watching shows recommended by AI. Its easy to see how AI makes daily life easier, but as its influence grows, so too do the potential risks, and therefore the need to make sure AI is being developed and used responsibly.?

In the absence of industry wide standardized rules and principles for the ethical and responsible use of AI, who should make decisions about what is an isn’t ok? Is it consumers? The companies developing AI? Regulatory bodies? Governments?

?In 2021, the European Commission published its proposal for a draft AI Act in an attempt to comprehensively regulate and set standards for the development of secure, trustworthy and ethical AI.? Final ratification is likely?to happen in?late 2022 – early?2023,??following several years of consultation.?Though the proposed regulation will evolve and ?continue to?codify best practices already adopted by AI leaders,?early adopters?have the opportunity to?differentiate and accelerate their AI capability?.

The proposed regulation, if approved, will apply to “AI systems,” – a broad definition that includes software which can, for a set of human-defined objectives- , generate outputs such as content, predictions, recommendations, or decisions influencing the environments they interact with.

Software qualifies as an “AI system” if it is developed using one/more of the following approaches/techniques:

???????Machine learning approaches, including supervised, unsupervised, and reinforcement learning, using a wide variety of methods including deep learning;

???????Logic- and knowledge-based approaches, including knowledge representation, inductive (logic) programming, knowledge bases, inference/deductive engines, (symbolic) reasoning and expert systems; and/or

???????Statistical approaches, Bayesian estimation, and search and optimization methods.

The proposed regulation does not apply to “AI systems” developed or used exclusively for ?military purposes, or to public authorities of third countries or international organisations where “AI systems” are used as part of an international agreement for law enforcement with the EU or with one or more Member States.

The proposed regulation applies to providers of AI systems (the developer that offers the AI system on the market) and users of AI systems (using an AI system under its authority) as follows:

???????EU and non-EU providers that place AI systems on the EU market;

???????EU users of AI systems; and

???????Providers and users of non-EU AI systems, if the output of the AI system is used in the EU.

The proposed regulation, if approved, will differentiate between uses of AI according to four different risk categories, based on four levels of risk posed to European values, established based on the level of impact on fundamental rights:

???????Unacceptable/Prohibited: Prohibiting certain AI systems as unacceptable uses of AI including social scoring, non-authorised use of biometric identification systems, manipulative use cases, exploiting vulnerabilities of individuals or groups.

???????High: Imposing extensive requirements on high-risk AI systems that affect Health & Safety of human and fundamental rights such as ?discrimination or putting humans at physical risk.

???????Limited: Imposing specific transparency obligations on certain AI systems to make users aware that they are interacting with an AI system to prevent the risk of manipulation

???????Minimal: Imposing minimal requirements on low-risk AI systems. Providers may voluntarily choose to create and implement codes of conduct which apply the EU’s proposed requirements for high-risk AI systems.

The proposed regulation echoes existing Responsible AI best practices like robust risk management, mature data governance, record keeping, traceability, transparency and monitoring to name a few. Based on these best practices, organisations should strategically focus on building broader Responsible AI capabilities, rather than just focusing on ?regulatory requirements. Organizations should see this proposed regulation as the catalyst to move from reactive compliance, to the proactive development of mature Responsible AI capabilities that will generate wider value.

?Through our work helping leading organisations develop robust RAI capabilities, Accenture has developed a comprehensive Responsible AI Methodology, which is used to help organizations work through the the four pillars of Responsible AI (Principles + Governance, Risk Policy and Controls, Technical, Cultural).?Each pillar has a series of interlocking steps that can be taken, and organizations work through these steps and pillars to strengthen their Responsible AI capabilities. When organizations have this framework in place they’ll be well set up to address any new regulation and assess its impact on their business without starting from scratch each time.?Stay tuned for our upcoming research, that will share more detail on this approach, and practical guidance for organizations to help prepare for the forthcoming regulations. ?

Authors –

Rudraksh (Rudy) Bhawalkar is an Analytics practitioner by core and currently works as Principal Director within Accenture Applied Intelligence as part of the Solution Design team. He is also leading the Responsible AI, Sustainability, Compliance and Data Protection capability in Austria, Switzerland & Germany across all industries. He has more than 14+ years of experience in the field of Data, Analytics and Artificial Intelligence covering Delivery, Sales, Pre-Sales and Solution Architecture. He is also a publisher of more than 40 articles on the topic of Artificial Intelligence, Analytics, IOT, Big Data, Digital Transformation along with being a Public Speaker at various CXO conferences in Europe, Americas, Africas and India.

Ray Eitel-Porter is Accenture’s Global Lead for Responsible AI, based in London. He joined Accenture in 2013 and has worked across a number of industries, mainly focusing on analytics strategy and operating model projects, and in the last three years developing Accenture’s solutions for data and AI ethics and advising clients in this area. Ray led the formation of Accenture’s Strategic Partnership with The Alan Turing Institute, the UK’s national institute for data science and artificial intelligence, to further research and innovation applied to real-world business challenges. He chairs the government’s Data Skills Taskforce and led the creation of a national data science prize for schools, in association with TeenTech, to excite interest at an early age in the possibilities that a training/career in data science can offer. Ray holds an MA in Modern Languages from Christ Church, Oxford as well as an MBA from INSEAD.

Disclaimer - Nothing in this article should be construed as legal advice and this article is not intended to be a substitute for legal counsel on any subject matter.?Accenture is not licensed to provide, nor should be regarded as providing, any legal or accounting or related services.