Artificial Intelligence: Risks, Regulation, and Global Responses

Artificial Intelligence: Risks, Regulation, and Global Responses
Artificial Intelligence: Risks, Regulation, and Global Responses

Ongoing developments of AI 

According to Goldman Sachs Research, ongoing Artificial Intelligence (AI) advancements are expected to generate significant economic impacts. The forecast suggests that AI will begin to show a measurable influence on the US Gross Domestic Product (GDP) by 2027, with subsequent effects on the growth trajectories of other global economies. The foundation of this outlook is based on the fact that AI has the potential to automate approximately 25% of labor tasks in advanced economies and 10-20% in emerging economies, as highlighted in a report by Goldman Sachs economists Joseph Briggs and Devesh Kodnani. Their projections indicate a positive boost to GDP growth from AI, with an estimated increase of 0.4 percentage points in the US, 0.3 percentage points on average in other Developed Markets (DMs), and 0.2 percentage points on average in advanced Emerging Markets (EMs) by the year 2034. 

In other emerging markets, the anticipated impact of AI might be more gradual, with a minor boost forecasted due to a potentially slower adoption rate and lower AI exposure.

Artificial intelligence benefits

Artificial Intelligence (AI) is revolutionizing multiple sectors, bringing unprecedented advancements: 

  • AI enhances diagnostic capabilities and personalized treatment plans and accelerates drug discovery processes in healthcare. 
  • Businesses leverage AI for data-driven decision-making, streamlining operations, and improving customer experiences.
  • In criminal justice, AI helps law enforcement in predictive policing, forensic analysis, and managing datasets to ensure a more effective and equitable legal system. 
  • The military sector benefits from AI in strategic planning, risk assessment, and autonomous systems that enhance awareness while minimizing human risk. 
  • In education, AI is transforming learning experiences through personalized tutoring, adaptive assessments, and data-driven insights to personalize educational approaches for individual students. 

Artificial intelligence risks

As the integration of Artificial Intelligence (AI) continues to reshape many industries, it is essential to recognize the associated risks: 

  • Lack of transparency poses another challenge; as complex AI systems can operate, it becomes difficult to understand their decision-making processes. 
  • Privacy concerns: AI systems often require vast amounts of personal data, raising questions about how this information is collected, stored, and used. 
  • Ethical considerations surrounding AI involve decisions made by machines that may lack a human sense of morality, sparking debates on the ethical implications of AI applications. 
  • The potential for job displacement is a significant worry, especially in industries where automation can replace specific human tasks, potentially leading to unemployment or shifts in the job market. 
  • The rise of misinformation facilitated by AI through deep fakes or algorithmic manipulation poses risks to public discourse and trust. 
  • Lastly, economic implications must be carefully monitored, as the adoption of AI may create disparities and inequalities, impacting specific sectors while benefiting others. 

Global responses for rapid regulations

AI's potential benefits and risks have led to widespread calls for governments to adapt quickly to the changes AI delivers and the potentially transformative changes. 

Leading figures

Sundar Pichai, Google's CEO, is an influential technology figure who has voiced concerns about the potential adverse effects of AI and advocated for establishing a suitable regulatory framework.


US President Joe Biden recently issued an executive order requiring AI manufacturers to provide the federal government with an assessment of their applications' vulnerability to cyber-attacks, the data used to train and test the AI, and its performance measurements.


Meanwhile, China's AI regulations substantially focus on generative AI and protections against deep fakes (synthetically produced images and videos that mimic the appearance and voice of real people but convey events that never happened). Chinese regulations ban fake news and restrict companies from employing dynamic pricing based on mining personal data for essential services to safeguard the public from unsound recommendations. Additionally, these regulations specify that all automated decision-making processes must be transparent to those directly affected.


On Mars 2023, the UK released a white paper detailing its approach to regulating AI. The document is based on five fundamental principles: 

Safety and security: AI systems should operate securely and safely, with a continuous process of identifying, assessing, and managing risks.

Transparency: AI systems must be transparent and answerable, facilitating comprehension and interpretation of their outputs.

Fairness: AI systems should not discriminate, generate an unfair outcome, or undermine legal rights. 

Accountability: AI should establish oversight and clear lines of accountability. 

Contestability: Users should have the possibility to contest AI decisions or outcomes


The Spanish AEPD, the independent supervisory authority whose primary objective is to monitor and ensure that European institutions and bodies respect the right to privacy and data protection when they process personal data and develop new policies, has implemented Audit Requirements for Personal Data Processing Activities involving AI


The French CNIL, the independent French administrative regulatory body whose mission is to ensure that data privacy law is applied to collecting, storing, and using personal data, has created a department dedicated to AI with open self-evaluation resources for AI businesses.


In April of 2021, the European Commission released the AI Act, a legislative proposal drafting regulations for the governance of AI within the European Union. The AI Act introduces a new approach, categorizing AI into four risk levels: unacceptable risk, high risk, limited risk, and minimal risk. The rules governing AI systems within the EU vary based on the perceived risk level towards fundamental rights.

Unacceptable risk

AI systems threatening individuals' safety, livelihoods, and rights will be outright banned. This includes applications such as governmental social scoring and voice-assisted toys that promote dangerous behavior.

High risk

AI systems identified as high-risk contain technologies used in critical infrastructures (transport), educational or vocational training (exam scoring), safety components of products (AI in robot-assisted surgery), employment and management (CV-sorting software), essential private and public services (credit scoring denying loans), law enforcement ( evaluating evidence reliability), migration and border control (document authenticity verification), and administration of justice and democratic processes. Strict laws must be met before high-risk AI systems can enter the market.

Limited risk

AI systems that are considered limited risk are subject to specific transparency obligations. Users interacting with AI systems, such as chatbots, must be informed that they are engaging with a machine, allowing them to make informed decisions about continuing or disengaging.

Minimal or no risk

The proposal permits the unrestricted use of minimal-risk AI, covering applications like AI-enabled video games or spam filters. Most AI systems currently employed in the EU fall into this low-risk category.

  • 2023

In 2023, the EU Council and the European Parliament changed the initial draft legislation, citing concerns regarding emerging technologies like ChatGPT, which introduce many potential applications and present new associated risks.

Therefore, the European Parliament conveyed that its Members had introduced alterations to the previous list of systems deemed to pose an unacceptable risk to people's safety

The changes now include bans on intrusive and discriminatory uses of AI, such as "real-time" remote biometric identification systems in public spaces. The scope of high-risk areas has been broadened to contain potential harm to people's health, safety, fundamental rights, or the environment. 

Additionally, AI systems influencing voters in political campaigns and recommender systems employed by social media platforms have been added to the high-risk category.

The finalization of the AI Act is expected to be reached by late 2023 or early 2024.

The way forward

The primary goal of regulation efforts is to find a balance between the need to regulate the development of AI, especially its impact on citizens' daily lives, and the need to avoid repressing innovation or burdening companies with rigid and strict laws. 

Assessing the potential success of the regulatory efforts takes work and time, as addressing such matters demands specific technical competence to understand what is being regulated and what should be regulated. 

Companies employing AI across diverse sectors will also encounter challenges in implementing a consistent and sustainable global approach to AI governance and compliance due to varying regulatory standards. 

Therefore, it's essential to prompt action, given that regulators have globally issued comprehensive guidance on AI regulation. Businesses using AI should navigate regulatory frameworks and strike a balance between compliance and innovation. They should also evaluate the regulations' implications for their activities and determine whether existing governance strategies align with the proposed principles. 

Overall, the success of regulatory efforts hinges on collaboration with regulators, transparent communication, and proactivity. 


What economic impacts are expected from ongoing AI advancements?

According to Goldman Sachs Research, AI advancements are forecasted to significantly impact the economy, showing measurable influence on the US GDP by 2027. AI is expected to automate about 25% of labor tasks in advanced economies and 10-20% in emerging economies, leading to a boost in GDP growth.

How will AI affect GDP growth in different regions?

  • US: An estimated increase of 0.4 percentage points in GDP growth by 2034.
  • Developed Markets (DMs): An average increase of 0.3 percentage points.
  • Advanced Emerging Markets (EMs): An average increase of 0.2 percentage points.
  • Other Emerging Markets: A more gradual impact is expected due to slower adoption rates and lower AI exposure.

What are the benefits of Artificial Intelligence (AI)?

AI brings significant advancements across various sectors:

  • Healthcare: Enhances diagnostic capabilities, personalized treatment plans, and accelerates drug discovery.
  • Business: Enables data-driven decision-making, streamlines operations, and improves customer experiences.
  • Criminal Justice: Assists in predictive policing, forensic analysis, and effective legal system management.
  • Military: Aids in strategic planning, risk assessment, and the development of autonomous systems.
  • Education: Personalizes learning experiences through adaptive tutoring and assessments.

What are the risks associated with AI integration?

  • Lack of transparency: Complex AI systems can make it difficult to understand their decision-making processes.
  • Privacy concerns: AI systems require vast amounts of personal data, raising concerns about data collection, storage, and usage.
  • Ethical considerations: Machines may make decisions without human morality, sparking ethical debates.
  • Job displacement: Automation could replace human tasks, leading to unemployment or shifts in the job market.
  • Misinformation: AI can facilitate the spread of deep fakes or algorithmic manipulation, threatening public trust.
  • Economic implications: AI adoption may create disparities and inequalities across different sectors.

How are global responses addressing AI regulation?

Governments worldwide are implementing various regulations to manage the potential benefits and risks of AI:


  • President Joe Biden issued an executive order requiring AI manufacturers to provide assessments of their applications' cybersecurity vulnerabilities, data usage, and performance measurements.


  • Regulations focus on generative AI and protections against deep fakes. Bans on fake news, dynamic pricing based on personal data, and mandates for transparent automated decision-making processes are included.


  • The UK's approach to AI regulation is based on five principles: safety and security, transparency, fairness, accountability, and contestability.


  • The Spanish AEPD implements audit requirements for personal data processing activities involving AI.


  • The French CNIL has created a department dedicated to AI, offering self-evaluation resources for AI businesses.


  • The AI Act categorizes AI into four risk levels: unacceptable, high, limited, and minimal risk. Regulations vary based on the perceived risk level, with bans on high-risk applications and transparency obligations for limited-risk systems.

What is the purpose of AI regulations?

The primary goal of AI regulations is to balance the need to control AI development's impact on citizens' daily lives with avoiding stifling innovation or burdening companies with overly strict laws. Effective regulation requires specific technical competence and collaboration with regulators.

What challenges do companies face with AI governance and compliance?

Companies must navigate varying global regulatory standards, ensuring their AI governance strategies align with proposed principles. They need to balance compliance with innovation while maintaining transparent communication and proactivity.

What is the expected outcome of the AI Act in the EU?

The finalization of the AI Act is anticipated by late 2023 or early 2024. The Act introduces a comprehensive framework for AI regulation, including bans on certain high-risk applications and requirements for transparency and fairness in AI systems.

How should businesses approach AI regulation?

Businesses should engage in transparent communication with regulators, proactively address compliance requirements, and evaluate the implications of regulations on their activities. They must balance innovation with ethical responsibility and align their governance strategies with regulatory frameworks.

What are the key takeaways for the future of AI regulation?

The success of AI regulatory efforts hinges on collaboration with regulators, transparent communication, and proactive measures. Businesses must navigate complex regulatory landscapes while fostering innovation and ensuring ethical AI development.

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