AI Adoption: Challenges and Resolutions for Governments

Published on October 05, 2023

The landscape of governmental agencies has long been marred by criticisms concerning limited public access to policy information and delays in processing claims.

Moreover, the perception of the public sector lagging behind its private sector counterparts in technological advancements has been a prevailing concern.

However, there is promising news on the horizon.

In 2021 (the latest data available), Gartner reported that 36% of government respondents in the US intended to boost their investments in AI and machine learning.

I previously explored the numerous positive functions of AI solutions, ranging from addressing public health challenges to predicting risks for social issues (and everything else in between)

But today, I will focus more on the challenges and regulations of AI adoption.

Most common challenges

  1. Regulatory issues: Governmental agencies operate within a complex framework of regulations and laws. When implementing AI solutions, they must ensure compliance with data protection, privacy, and other relevant regulations. This can create hurdles in the deployment of AI systems, as agencies must navigate the legal landscape to ensure the responsible and ethical use of AI.
  2. PR concerns: Introducing AI solutions in the public sector can raise public concerns about privacy, job displacement, and potential biases in decision-making algorithms. Lack of transparency and public awareness about the use of AI may lead to misconceptions and negative perceptions, affecting the reputation of the agency.
  3. Staff resistance to change: Employees in public agencies may be resistant to adopting new technologies due to fear of job displacement, lack of understanding of AI’s potential benefits, or the perception that AI might replace human judgment. Overcoming this resistance requires effective communication, training, and involvement of staff in the adoption process.
  4. Project delays and failures: Implementing AI solutions in the public sector can be complex and time-consuming. Projects may face delays due to bureaucratic processes, budget constraints, or unforeseen technical challenges. Moreover, failure to properly plan and execute AI initiatives can lead to wasted resources and missed opportunities for efficiency gains.
  5. Cybersecurity risks: With the increasing use of AI, public agencies become attractive targets for cyberattacks. The large volumes of sensitive data they handle, coupled with the potential vulnerabilities of AI systems, make them susceptible to data breaches and other cyber threats. Ensuring robust cybersecurity measures is crucial to safeguard public information and maintain trust.

Addressing these challenges requires a comprehensive approach, including:

●      Regulatory compliance: Engaging legal experts to ensure adherence to relevant regulations and ethical guidelines.

●      Transparent communication: Educating the public about AI’s potential benefits, risks, and safeguards to build trust and mitigate PR concerns.

●      Employee training: Providing adequate training and support to employees to embrace AI as a tool to enhance their work and not replace them.

●      Efficient project management: Employing experienced project managers to streamline the implementation process and manage potential delays effectively.

●      Robust cybersecurity measures: Implementing strong cybersecurity protocols to safeguard data and prevent breaches or attacks.

Setting the scene for the future of AI

The draft European Union Artificial Intelligence Act, recently agreed upon in the European Parliament, is considered one of the most comprehensive and radical steps towards AI regulation globally.

It is anticipated that the final Act will be passed later this year, carrying significant implications for international regulatory standards.

Despite being the world’s third-largest economy, the European Union prioritizes human rights over technological advantage.

One of the key features of the draft EU AI Act is the introduction of three risk categories for AI models. Under this framework, AI systems deemed to pose an unacceptable risk will be banned.

For instance… the Act aims to prohibit the implementation of AI-enabled systems like China’s social credit or social-scoring regime within the EU.

Additionally, the Act seeks to restrict the use of “real-time” biometric identification systems in public spaces for law enforcement purposes across the EU.

By doing so…the Act intends to protect individuals’ rights and privacy.

This legislative development showcases the EU’s commitment to striking a balance between harnessing AI’s potential and safeguarding fundamental rights.

Final thoughts

As someone who believes in the potential of AI to positively impact society, I appreciate the EU’s cautious and measured approach to AI regulation.

By carefully considering the ethical implications and social consequences of AI implementations, the EU is setting a precedent for responsible AI governance that can inspire other regions to follow suit.

As the Act moves towards finalization, its impact on shaping AI regulations worldwide will be closely observed.


About the Author

Mohammad J Sear is focused on bringing purpose to digital in government.

He has obtained his leadership training from the Harvard Kennedy School of Government, USA and holds an MBA from the University of Leicester, UK.

After a successful 12+ years career in the UK government during the premiership of three Prime Ministers Margaret Thatcher, John Major and Tony Blair, Mohammad moved to the private sector and has now for 20+ years been advising government organizations in the UK, Middle East, Australasia and South Asia on strategic challenges and digital transformation.

He is currently working for Ernst & Young (EY) and leading the Digital Government practice efforts across the Middle East and North Africa (MENA), and is also a Digital Government and Innovation lecturer at the Paris School of International Affairs, Sciences Po, France.

As a thought-leader some of the articles he has authored include: “Digital is great but exclusion isn’t – make data work for driving better digital inclusion” published in Harvard Business Review, “Holistic Digital Government” published in the MIT Technology Review, “Want To Make Citizens Happy – Put Experience First” published in Forbes Middle East.

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