U.S. government investment in artificial intelligence (AI), which amounted to $4.38 billion in 2022, is designed to benefit not only national security and government operations but also American society. This two-pronged approach has led to discoveries about the advantages of AI in areas beyond governance, including healthcare, transportation, the environment, and others.

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Starting with an endorsement of “man-machine cooperation” by then-President John F. Kennedy’s Science Advisory Committee in 1962, numerous presidential administrations have encouraged AI research and knowledge, including in the workforce, education, and government. These efforts included an Obama administration 2016 report titled “Preparing for the Future of Artificial Intelligence;” the Trump administration’s “American AI Initiative,” launched in 2019; and the Biden administration’s executive order on the “Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence,” issued in October 2023.234

As AI technology advances, the government is exploring ways to harness and leverage it in its operations while setting and maintaining appropriate guardrails.

AI Initiatives in the U.S. Government

President Joe Biden’s October 2023 executive order (EO) on the “Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence” provides extensive guidance for government involvement in AI.5

Primary Directives

The Biden EO directs U.S. government agencies to establish safety and security standards, protect privacy, advance equity and civil rights, promote innovation and competition, and advance American AI leadership worldwide. An overview of the document’s eight primary directives follows.654

New Standards for AI Safety and Security

The EO directs government agencies to ensure robust, reliable, repeatable, and standardized testing and evaluations of AI systems. The administration will also help develop adequate labeling and mechanisms to ensure the origin of AI content.

Promoting Innovation and Competition

AI-related education, training, development, research, and capacity investments must be leveraged to address specific intellectual property (IP) questions. Agencies must promote competition by providing small developers access to technical assistance and encouraging the Federal Trade Commission (FTC) to exercise its authority to enforce competition and protect consumers.

Supporting Workers

Government departments must develop principles and best practices to mitigate the harms and maximize the benefits of AI for workers. This will require addressing job displacement, labor standards, workplace equity, health and safety, and data collection.

Advancing Equity and Civil Rights

Government use of AI will comply with all federal laws and promote substantive oversight and engagement with all communities to protect against unlawful discrimination and abuse. Coordination between the U.S. Department of Justice (DOJ) and federal civil rights offices will play a significant role in these efforts.

Standing Up for Consumers, Patients, and Students

To protect consumers and promote the responsible use of AI in domains such as healthcare and education, the administration will enforce existing consumer protection laws and enact safeguards against fraud, unintended bias, privacy violations, and other harmful effects. This will include advancing the responsible use of AI in developing affordable and lifesaving drugs and advancements in other health-related areas.

Protecting Americans’ Privacy

The lawful, secure collection, use, and retention of data must promote privacy by directing federal agencies to use privacy-enhancing technologies (PETs) where beneficial. Congress is also urged to pass bipartisan data privacy legislation.

Ensuring Responsible and Effective Government Use of AI

Agencies will ensure the responsible government deployment of AI and work to modernize federal AI infrastructure in various domains, such as regulation, governance, benefits, procurement, and security. The government will further accelerate hiring AI professionals as part of a government-wide AI talent surge led by the Office of Personnel Management, the U.S. Digital Service, the U.S. Digital Corps, and the Presidential Innovation Fellowship.

Advancing American Leadership Abroad

Government agencies are directed to engage with international partners to develop a framework to manage AI risks while advancing American leadership in safety, security, trust, and AI development. This will include the expansion of bilateral, multilateral, and multistakeholder collaborations on AI; accelerated development and implementation of vital AI standards with international partners; and promoting safe, responsible, rights-affirming development and deployment of AI worldwide.

AI Initiatives and Projects in Government Agencies

President Biden’s October 2023 executive order mandates U.S. government agencies to pursue various AI initiatives. For example, the president directed the organization of an interagency council to coordinate AI development, assess the ability of federal agencies to adopt AI, and address national security risks and benefits.4

Highlights of the main initiatives for different agencies are shown in the table below.

Ensuring Responsible Use of AI in Government

Government agencies regularly call for the responsible use of AI. This includes mandates for compliance with laws that protect privacy, civil rights, and civil liberties. The benefits of AI come with potential pitfalls that create a need to establish strong guardrails to ensure AI keeps people safe and doesn’t violate individual rights.

AI Safety and Security

Section 4 of the Biden EO addresses AI system vulnerabilities through the Defense Production Act of 1950. AI companies must report safety test results and other information for systems that may pose national security or infrastructure risks. Federal agencies must establish guidance and standards for safe AI development and use and promote research and collaboration to address potential risks. Workforce development plans for integrating AI technology are also required.4

Ethical Considerations and Privacy Concerns

AI has raised ethical concerns about privacy, bias, accountability, and transparency. Despite ideological differences between administrations, government AI policies have attempted to address these concerns since 2016. AI systems require large amounts of data, which can raise privacy concerns. Bias can result from training AI systems on non-representative data, leading to discriminatory outcomes. AI decisions can have significant impacts on individuals, making accountability critical. The transparency of AI decision-making processes is also important for individuals to understand how and why decisions are made.4

Benefits of Artificial Intelligence in Government Services

AI can offer several benefits to the government, such as improved efficiency, accuracy, and decision making. AI can automate repetitive tasks, freeing up employees to focus on higher-value tasks. AI can eliminate errors and inconsistencies for improved accuracy and consistency of government services. AI can facilitate data-driven and evidence-based decisions, as well as personalized and responsive services. Additionally, AI can save costs by reducing the need for manual labor and streamlining processes.68

AI has shown benefits in specific areas, such as healthcare, transportation, the environment, and delivery of government benefits. HHS leverages AI to solve problems and improve patient outcomes. The DOT uses AI in three areas: drone operations, traffic management, and railroad safety. AI is used in the environment to monitor natural resources and predict natural disasters. AI can also reduce the workload for workers and assist caseworkers. The Social Security Administration (SSA) uses data analytics and computer systems to process claims more efficiently.910111213

Challenges and the Future of AI in Government Services

AI constantly evolves, and potential advancements include improving accuracy and efficiency, creating more human-like systems, personalizing medicine, and addressing global challenges.

However, implementing AI in government services has several challenges, such as a lack of skilled personnel, data privacy and security concerns, integration with existing systems, and transparency and accountability. Addressing these challenges requires a collaborative approach involving government agencies, AI developers, domain experts, and citizens. Governments need to invest in training, establish clear policies and guidelines, and engage citizens to build trust and ensure accountability.

The Bottom Line

The potential of AI to transform government services and improve public welfare is immense. AI can help streamline bureaucratic processes, enhance decision-making capabilities, and enable more efficient delivery of public services.

For example, AI-powered chatbots can provide 24/7 customer support, reducing wait times and improving the overall experience for citizens. AI can also be used to analyze vast amounts of data to identify patterns and trends, which can inform policy decisions and resource allocation.

By harnessing the power of AI, the government can enhance its capacity to serve its citizens and improve the overall well-being of its communities. Additionally, the use of AI in government services may be imperative to achieve efficiency, accuracy, and cost containment, especially as both the number of government services and the population continue to expand.

While advantages of AI—especially in healthcare, transportation, the environment, and benefits delivery—are numerous, responsible use of AI in government requires establishing strong guardrails and addressing ethical and privacy concerns.

KEY TAKEAWAYS

Artificial general intelligence (AGI) is a branch of theoretical artificial intelligence (AI) research working to develop AI with a human level of cognitive function, including the ability to self-teach. However, not all AI researchers believe that it is even possible to develop an AGI system, and the field is divided on what factors constitute and can accurately measure “intelligence.”12

Other terms for AGI include strong AI or general AI. These theoretical forms of AI stand in contrast to weak or narrow AI, which can perform only specific or specialized tasks within a predefined set of parameters. AGI would be able to autonomously solve a variety of complex problems across different domains of knowledge.2

What Is Artificial General Intelligence (AGI)?

Opinions differ as to how AGI might eventually be realized since it remains a theoretical concept. According to AI researchers Ben Goertzel and Cassio Pennachin, “‘general intelligence’ does not mean exactly the same thing to all researchers.”3

However, “loosely speaking,” AGI refers to “AI systems that possess a reasonable degree of self-understanding and autonomous self-control, and have the ability to solve a variety of complex problems in a variety of contexts, and to learn to solve new problems that they didn’t know about at the time of their creation.”3

Because of the nebulous and evolving nature of both AI research and the concept of AGI, there are different theoretical approaches to how it could be created. Some of these include techniques such as neural networks and deep learning, while other methods propose creating large-scale simulations of the human brain using computational neuroscience.4

Key Approaches in AGI Research

Computer scientists and artificial intelligence researchers continue to develop theoretical frameworks and work on the unsolved problem of AGI. Goertzel has defined several high-level approaches that have emerged in the field of AGI research and categorizes them as follows:

• Symbolic: A symbolic approach to AGI holds the belief that symbolic thought is “the crux of human general intelligence” and “precisely what lets us generalize most broadly.”
• Emergentist: An emergentist approach to AGI focuses on the idea that the human brain is essentially a set of simple elements (neurons) that self-organize complexly in reaction to the experience of the body. In turn, it might follow that a similar type of intelligence might emerge from re-creating a similar structure.
• Hybrid: As the name suggests, a hybrid approach to AGI sees the brain as a hybrid system in which many different parts and principles work together to create something in which the whole is greater than the sum of its parts. By nature, hybrid AGI research varies widely in its approaches.
• Universalist: A universalist approach to AGI centers on “the mathematical essence of general intelligence” and the idea that once AGI is solved in the theoretical realm, the principles used to solve it can be scaled down and used to create it in reality.5
  

Comparing AGI and AI: What's the Difference?

While AI encompasses a vast range of technologies and research avenues that deal with machine and computer cognition, AGI (or AI with a level of intelligence equal to that of a human) remains a theoretical concept and research goal. 

AI researcher Peter Voss defines general intelligence as having “the ability to learn anything (in principle).” Under this criteria, AGI’s learning ability would need to be “autonomous, goal-directed, and highly adaptive.” AGI is generally conceptualized as being AI that can match the cognitive capacity of humans and is categorized under the label of strong AI.6

In comparison, most of the AI available at this point would be categorized as weak or narrow AI, as it was developed to focus on specific tasks and applications. It’s worth noting that these AI systems can still be incredibly powerful and complex, with applications ranging from autonomous vehicle systems to voice-activated virtual assistants; they merely rely on some level of human programming for training and accuracy.2

Predicting the Future of AGI: Insights and Possibilities

The year when we will be able to achieve AGI (or whether we will even be able to create it at all) is a topic of much debate. Several notable computer scientists and entrepreneurs believe that AGI will be created within the next few decades:

• Louis Rosenberg, CEO and chief scientist of Unanimous AI, predicted in 2020 that AGI would be achieved by 2030.7
• Ray Kurzweil, Google’s director of engineering and a pioneer of pattern recognition technology, believes that AI will reach “human levels of intelligence” in 2029 and surpass human intelligence by 2045.8
• Jürgen Schmidhuber, co-founder and chief scientist at NNAISENSE and director of Swiss AI lab IDSIA, estimates AGI by around 2050.

The future of AGI remains an open-ended question and is an ongoing research pursuit. Some scholars even argue that AGI cannot and will never be realized. AI researcher Goertzel explained that it’s difficult to objectively measure the progress toward AGI, as “there are many different routes to AGI, involving integration of different sorts of subsystems” and there is no “thorough and systematic theory of AGI.” Rather, it’s a “patchwork of overlapping concepts, frameworks, and hypotheses” that are “often synergistic and sometimes mutually contradictory.”
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Sara Hooker of research lab Cohere for AI told Wired, “It really is a philosophical question. So, in some ways, it’s a very hard time to be in this field, because we’re a scientific field.”10

Early Instances and Future Examples of AGI

Because AGI remains a developing concept and field, it is debatable whether any current examples of AGI exist.

Researchers from Microsoft (MSFT), in tandem with OpenAI, claim that GPT-4 “could reasonably be viewed as an early (yet still incomplete) version of an AGI system.” This is due to its “mastery of language” and its ability to “solve novel and difficult tasks that span mathematics, coding, vision, medicine, law, psychology and more, without needing any special prompting” with capabilities that are “strikingly close to human-level performance.”11 However, Sam Altman, CEO of ChatGPT, says that ChatGPT is not even close to an AGI model.

In the future, examples of AGI applications might include advanced chatbots and autonomous vehicles, both domains in which a high level of reasoning and autonomous decision making would be required.

The Bottom Line

The concepts of AI and AGI have long captured the human imagination, and explorations of the ideas abound in stories and science fiction. Recently, scholars have argued that even mythology dating from as far back as ancient Greece can be seen to reflect our fascination with artificial life and intelligence.13

There are currently many different approaches toward creating AI that can think and learn for itself and apply its intelligence outside the bounds of a previously specified range of tasks. Due to the theoretical and multifaceted nature of this research, it is difficult to say if and when AGI might be achieved. However, if it does become a reality, one thing is certain: It will have fundamental and wide-ranging impacts across our technologies, systems, and industries.