Artificial Intelligence: An Accountability Framework for Federal Agencies and Other Entities

As a result, their task backlogs keep piling up, causing further delays in government workflows. For instance, during the pandemic, AI impacted the detection and control of the COVID-19 virus. Separately, Acemoglu warned, if private companies or central governments anywhere in the world amass more and more information about people, it is likely to have negative consequences for most of the population. The event included a commentary from Fotini Christia, the Ford International Professor of the Social Sciences and director of the MIT Sociotechnical Systems Research Center.

Agencies and policymakers can leverage artificial intelligence to conduct citizen-centric smart policymaking. AI tools provide advanced analytics on public data, allowing policymakers to identify emerging issues related to their regions and constituents. Any intrusion in government databases affects national security and damages the public’s trust. Thanks to technological advancements like computer vision, object detection, drone tracking, and camera-based traffic systems, government organizations can analyze crash data and highlight areas with a high likelihood of accidents.

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It is common to have different views on what fair means, so incorporating those views through consultations with customers and early mitigating protocols prior to deploying the AI system, helps with acceptance and smooth operations. Likewise, it is common to identify bias in training data at design and deployment time. Engineering practice has progressed a lot lately and allows practitioners to train on edge cases, try different ML models, and provide sufficient guidance and education on modelling so that everyone in the organisation has a stake in ensuring the model is working as intended and makes sense. However, we shall not expect our AI systems to be completely bias-free and fair for all. We look forward to collaborating with key stakeholders in federal and state government, nonprofit research, and community-based group collaborators to ensure the outsize benefits and large-scale risks of automated systems are distributed equitably. Please reach out to Rita Ko ([email protected]) to share your interest in partnering with the Urban Institute to evaluate and implement more equitable and impactful algorithmic systems.

One of the biggest benefits of Artificial Intelligence is that it can significantly reduce errors and increase accuracy and precision. The decisions taken by AI in every step is decided by information previously gathered and a certain set of algorithms. Before we jump on to the advantages and disadvantages of Artificial Intelligence, let us understand what is AI in the first place. From a birds eye view, AI provides a computer program the ability to think and learn on its own. It is a simulation of human intelligence (hence, artificial) into machines to do things that we would normally rely on humans. There are three main types of AI based on its capabilities – weak AI, strong AI, and super AI.

The Benefits of AI in State and Local Government Operations

(i)    The Secretary of Defense shall carry out the actions described in subsections 4.3(b)(ii) and (iii) of this section for national security systems, and the Secretary of Homeland Security shall carry out these actions for non-national security systems. Each shall do so in consultation with the heads of other relevant agencies as the Secretary of Defense and the Secretary of Homeland Security may deem appropriate. (ii)   Within 150 days of the date of this order, the Secretary of the Treasury shall issue a public report on best practices for financial institutions to manage AI-specific cybersecurity risks. Such reports shall include, at a minimum, the information specified in subsection 4.2(c)(i) of this section as well as any additional information identified by the Secretary. By automating routine interactions, governments can allocate human resources to more complex tasks, while ensuring citizens receive timely assistance.

NLP can also assist in automating routine tasks like document summarization and language translation, freeing up valuable time for policymakers to focus on more strategic initiatives. AI in the government can also help identify patterns and trends in data that may not be immediately apparent to human analysts. This can lead to more effective policies and programs that are based on evidence and have a higher likelihood of success. Compared to private sector organizations, government agencies face additional legal and risk constraints which can inhibit their ability to quickly adopt and deploy AI.

The Secretary of Transportation shall further encourage ARPA-I to prioritize the allocation of grants to those opportunities, as appropriate. The work tasked to ARPA-I shall include soliciting input on these topics through a public consultation process, such as an RFI. (G)  identification of uses of AI to promote workplace efficiency and satisfaction in the health and human services sector, including reducing administrative burdens. The report shall include a discussion of issues that may hinder the effective use of AI in research and practices needed to ensure that AI is used responsibly for research. (ii)  a public report with relevant data on applications, petitions, approvals, and other key indicators of how experts in AI and other critical and emerging technologies have utilized the immigration system through the end of Fiscal Year 2023.

Conversational AI use cases in citizen services

An ethical approach to AI is fundamental, but it constitutes a colossal challenge in legal thought. Indeed, the pace of development of AI is much faster than the pace of development of legal texts. In general, the conventional approach to regulating AI prompts the legal reflection that starts from a ‘principle’. For example, when authorities want to legislate on the use of data by AIs, they establish the principle of ‘invasion of privacy’ and apply this to all AIs that use data, without nuance.

• This adds to the intense policy design work at national level, which has originated so far.
• By utilizing NLP algorithms, government agencies can efficiently process and analyze vast amounts of text-based data, such as legislation, regulations, and public opinion.
• In contrast, roughly two-thirds of IT executives, presumably closer to implementation rhythms, see business operations getting new generative AI applications in the next 6-12 months, followed by case management cybersecurity use cases.
• EMMA guides around one million applicants per month regarding the various services offered by the department and directs them to relevant pages and resources.

The report on the use of automated decision-making in the Canadian immigration system, has caused a significant backlash and forced the government to reinvent its relation with the automated tools. Thanks to the pressure from academia and advocacies, some of the most controversial practices have been put to halt. AI is capable of learning over time with pre-fed data and past experiences, but cannot be creative in its approach.

This starts with a clear understanding of the limitations and blind spots of AI both among the creators/developers and the operators of such AI applications. Safeguards such as mechanisms for exception handling, human interventions, the ability to override AI decisions, human oversight, and governance are all part of Responsible AI. This has given rise to BigTech, which arguably has more power than many nations today. Similarly, in AI the odds favour the deep-pocketed companies because AI breakthroughs require massive amounts of data, huge computing power, and highly skilled talent.

It helps in intelligence sharing across different government agencies by identifying and tagging malicious entities. Similarly, the Department of Homeland Security, USA, uses EMMA, a virtual assistant catering to immigration services. EMMA guides around one million applicants per month regarding the various by the department and directs them to relevant pages and resources. In the UK, National Health Service (NHS) formed an initiative to collect data related to COVID patients to develop a better understanding of the virus.

Finally, the legislator will be able to distinguish the algorithmic biases according to the potential dangers and further extend the legislative logic. This logic would therefore not be exclusively based on a starting principle but, instead, on a societal and technical understanding of AI. Artificial intelligence is a unique technology — it has an impact on all aspects of society and sometimes simultaneously. Consequently, it questions our societies and sometimes upsets the organization of societies. Generally, it is the biases of certain AI systems that worry people and authorities and raise the need for an ethical approach to AI.

There is a need to ensure that this data is collected, stored, and used in a secure and privacy-conscious manner. Protecting patient privacy, maintaining data confidentiality, and preventing unauthorized access to personal health information are critical considerations. AI algorithms can analyze large volumes of medical data, including patient records, lab results, and medical images, to assist healthcare professionals in making accurate and timely diagnosis. AI can identify patterns and anomalies that may be difficult for human clinicians to detect, leading to earlier detection of diseases and improved treatment outcomes. Humans cannot develop artificial intelligence because it is a technology based on pre-loaded facts and experience.

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Conversely, Acemoglu noted, “There is every danger that overemphasizing automation is not going to get you many productivity gains either,” since some technologies may be merely cheaper than human workers, not more productive. To be sure, he noted, there are many, many ways society has ultimately benefitted from technologies. Similarly, Acemoglu observed, Eli Whitney’s invention of the cotton gin made the conditions of slavery in the U.S. even worse. That overall dynamic, in which innovation can potentially enrich a few at the expense of the many, Acemoglu said, has not vanished.

In recent years, I have become increasingly interested in the potential of artificial intelligence (AI) to help us achieve these goals. Leaders such as billionaire Elon Musk have sounded the alarm that the technology could lead to the destruction of civilization, noting that if humans become too dependent on automation they could eventually forget how machines work. Other tech executives have a more optimistic view about AI’s potential to help save humanity by making it easier to fight climate change and diseases. If anything, you may be understating the potential impact of AI, at least in the area of enhancing democracy and trust-building. AI’s use in citizen engagement and empowerment will scale far beyond “facilitation, information gathering, consensus building and idea generation” in carefully-managed citizen assemblies.

For example, the governance principle calls for users to set clear goals and engage with diverse stakeholders. However, Shorey is cautious about the possibility of artificial intelligence being brought into decision-making processes such as determining who qualifies for social service benefits, or how long someone should be on parole. Justice Department began investigating allegations that a Pennsylvania county’s AI model intended to help improve child welfare was discriminating against parents with disabilities and resulting in their children being taken away.

In reality, most of us encounter Artificial Intelligence in some way or the other almost every single day. From the moment you wake up to check your smartphone to watching another Netflix recommended movie, AI has quickly made its way into our everyday lives. According to a study by Statista, the global AI market is set to grow up to 54 percent every single year. Well, there are tons of advantages and disadvantages of Artificial Intelligence which we’ll discuss in this article. But before we jump into the pros and cons of AI, let us take a quick glance over what is AI. Use image data for modeling, with the ability to combine additional data types with your image data including text, tabular and audio data, with out-of-the-box access to all of the recent CNN-architectures and GPU accelerated training.

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