Privacy and Security challenges when using AI in project management
Artificial intelligence (AI) is becoming a mainstream technology. Its applications are growing across a wide range of disciplines, including (but not limited to) healthcare, environmental management, food security, agriculture, and business management. The launch of large language models such as ChatGPT has further accentuated the urge to integrate AI into solution development to solve problems faced by humanity.
While growth has been wide and varied, so have the challenges. The concerns about the morality of AI decision-making, bias, privacy, security of data used, and misuse of AI are increasing with every passing day. The lack of well-coordinated efforts and guidelines to regulate growth is only adding to piles of concerns. Just like other professions, project management is also impacted by a variety of issues when AI is used for project delivery purposes. Given that projects often result in unique outputs, the challenges could become extra sensitive.
Therefore, it is important to spell out the privacy and security challenges when using AI in project management. With that in mind, we point out some of the potential privacy and security challenges below. Needless to mention, the list is neither exhaustive nor conclusive by any means. Further, as privacy and security challenges shape, reshape, and reinvent themselves over a period of time, one needs to keep learning and adapting to deal with the new and not-so-new challenges on an ongoing basis.
Privacy and security challenges
1) Project employees’-oriented challenges
Employees’ surveillance or monitoring is becoming a serious challenge as AI tools become more sophisticated. According to a report (Lazar & Yorke, 2023), there is a considerable growth in the demand for employee surveillance tools. AI, thus, can be considered intrusive and could violate employees’ privacy rights.
The AI tools may be used to track and monitor project staff behaviors, work habits, performance, etc. This may lead to bias and discrimination. In some cases, it may result in taking punitive action against certain staff or showing leniency and providing undue benefits to others. It could create discontent and lower the morale of the team. AI may also be used to choose or prefer having people from certain demographics on high-value or prestigious projects, resulting in unfair treatment to those who were not selected.
Additionally, the internal functioning of the project team, collaboration patterns, and relationships could be analyzed using AI tools, which could reveal interpersonal dynamics. The development of such insights could be misused, causing mistrust and strained relationships.
2) Third party related challenges
Given the ad hoc nature of project work, using leased tools is often a common practice for performing project work. When AI tools are to be provided by external vendors, there is an opportunity that the vendors could access proprietory confidential information, which could result in a breach of private and confidential project information.
3) Decision bias
Often, historical data is used for estimation purposes in projects. It could be at the bidding stage as well as during the project planning and execution stages. If the AI model is trained on such data, its use will introduce bias in the decisions related to the current project. The same will be the case if the bias in the data is about project staff, which could potentially lead to resource allocation bias.
4) Data breaches
Recently, the news about several data breaches has amplified concerns about data security in general. This is also a potential issue when AI tools are used in project management. Where AI tools are used for task definition, estimation, and other various purposes, it entails risks of exposure to confidential information. In particular, where a project is of a high-stakes nature or created to design an innovative output, it raises further concerns about the security of task-related data and blueprints for how the project is to be carried out. The use of AI in such situations needs to be made secure to avoid any potential risks of data breaches.
5) Security audits
One of the predicaments that project organizations will face is that they may not always have the expertise to perform security audits of the AI systems that they use during project delivery. In situations where AI tools are integrated with project management tools, the lack of regular security audits could result in the non-detection of potential vulnerabilities and expose sensitive information about projects to hacking and other breaches.
6) Other challenges
Other oft-reported challenges, such as the black box nature of AI algorithms, appropriate access control, and secure integration of AI tools and project management systems, just to name a few, need to be dealt with as well.
As AI has become mainstream, there is a growing need to learn to deal with the challenges that come with its use. The complex nature of AI tools makes it even more important to learn to live with them by understanding the intricacies involved in the process. The challenges of using AI come in various forms, shapes, and varieties. Particularly, as projects are delivered in all types of contexts, often influenced by the parent organization’s culture and exposure to the use of AI, the use of AI for project management could face some unique and novel challenges.
Given that, we have looked at a few of them in this article. The intent is to highlight some of the broad challenges to becoming AI-ready when using it for project delivery purposes. While dealing with challenges is a moving target with a lot of uncertainty about the best way forward, one thing is certain: AI is becoming unavoidable, and there is a need to build awareness about its use and potential roadblocks. This article tries to achieve that in a little way, supposedly.
References: Lazar, W.S. & Yorke, C. (2023). Watched while working: Use of monitoring and AI in the workplace increases, https://www.reuters.com/legal/legalindustry/watched-while-working-use-monitoring-ai-workplace-increases-2023-04-25/
© 2024 Jiwat Ram, All Rights Reserved.
Jiwat is a Professor in Project Management. He has considerable experience of working internationally in diverse cultures and business environments.
He has a growing portfolio of work on issues related to artificial intelligence, machine learning and large language models (LLMs). His work has been published in top scientific journals.
Jiwat actively contributes to project management community. More recently, he has published a number of articles on some of the contemporary issues confronting project management and business management in various industry based outlets.
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