Three data and AI challenges government CIOs must get right

With the pace of technological innovation rapidly accelerating and a growing landscape of data and AI applications, government CIOs must learn how to leverage i...

The past year has kept us at the edge of our seats within both the private and public sectors. We saw an increase in the number of nefarious attacks on our nation’s most sensitive agencies, an unprecedented leap forward in AI innovation, and the continued expansion of the internet of things (IoT) at home, abroad and even in outer space. 

 With the pace of technological innovation rapidly accelerating and a growing landscape of data and AI applications, government CIOs must learn how to leverage innovations in both the public and private sectors, decide which of their technology investments should be kept and which need replacement, and determine how to ensure their teams are set up for success. 

 Like their counterparts in other industries, government CIOs must prioritize several key considerations when it comes to data and AI initiatives. Both can have a profound impact on government operations, citizen services and policymaking. But as data volumes grow, a recent study reported that trust in data quality is slipping. At the same time, there is a growing need to invest in new data warehousing technologies to improve data processing capabilities at scale. 

 To stay ahead in the ever-changing landscape of big data (and beyond), government CIOs must get three critical things right:  

  1. Data integrity and security

Maintaining data integrity and protecting sensitive citizen and government data are paramount. Government CIOs must ensure that robust cybersecurity measures are in place to safeguard data from breaches, cyberattacks and unauthorized access, all while ingesting and ensuring the trustworthiness of data from a growing number of sources and locations. 

 It is also important to establish clear data governance policies and practices for managing data access, sharing and retention. When considering the technology underlying these practices, organizations should opt for scalable data platforms that can reduce the need for data movement and replication.  

  1. Ethical use of AI and bias mitigation

Another key area for government CIOs to tackle is leveraging data and AI fairly to prevent discrimination against certain groups or individuals. As technology advances rapidly, there are ethical implications of AI algorithms and data intelligence that must be prioritized over innovation at all costs. Ensuring transparency while implementing bias mitigation techniques and conducting regular audits of AI systems are critical to ensuring public trust in the system. 

 All of this must be supported by effective data preparation, integration, transformation, and analytics capabilities. Government CIOs should also build diverse AI development teams to help mitigate ethical concerns.   

  1. Data interoperability and workforce development

One final challenge government CIOs must get right to succeed with data and AI is data interoperability and workforce development. It’s no secret that government agencies must operate in compartments at times, but as data volumes grow, building data repositories and workflows that can leverage data from a variety of sources will become a critical component in driving the accuracy and effectiveness of AI solutions. 

 Hand in hand with data interoperability is workforce development. Developing and implementing interoperable systems and AI solutions requires the right balance of tools, time and talent. This may mean greenlighting new public-private partnerships to leverage bleeding-edge technologies for the benefit of citizens. 

 In addition to these three challenges, government CIOs must hold themselves and their teams accountable for AI-driven decision-making processes, especially when they affect public policy and the lives of citizens. Public officials cannot hide behind the algorithms they have created. 

 As the saying goes, “with great power comes great responsibility,” and the growing power of AI is no different. Because government decisions often have far-reaching consequences, government CIOs should prioritize transparency and establish clear accountability frameworks for the development and review of AI systems. They must also define roles and responsibilities for handling data, developing new algorithms, and making data-driven decisions. 

 By addressing these challenges proactively and communicating regularly with the public, government CIOs can build trust and foster collaboration between the public sector and citizens. One thing is clear: The potential to leverage hyperscale data and AI to improve government services and positively impact the lives of citizens has never been greater. Establishing the right processes now will help ensure data and AI are used for good — today, and as the technology landscape continues to evolve. 

 Tony Ibáñez is a public sector solutions architect at Ocient. 

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