Artificial Intelligence Governance Part I

3 Mins read

In Part I of the article we will discuss the challenges facing AI Governance. It’s not a surprise that every new cyber product we come across has something to do with machine learning (ML) and artificial intelligence (AI). The subject AI is of interest to everyone and many organizations are likely to buy or have already bought AI products without understanding the larger implications of adopting AI. AI within the organization’s need to be governed by policies, procedures as well as other consideration such as ethics, accountability, and transparency. In addition, companies should understand that using AI in Human Resources will not cause issues with unfair bias and unjust impacts.

Gartner defines AI as “advanced analysis and logic-based techniques, including machine learning, to interpret events, support and automate decisions, and take actions.” The definition of ML from Stanford is “it is the science of getting computers to act without being explicitly programmed.” Simply put, ML is a sub-field of AI that includes techniques that enable machines to improve at tasks with experience.

For convenience in the article below we will refer systems employing AI, ML and Algorithms collectively as “AI.”

Briefly the advantages of AI includes:

  • Reduces human workloads
  • Increases precision in tasks
  • Processes large amounts of data in short time spans                                         
  • Improves the quality of lives
  • Complements/enhance human cognitive capabilities

The following are few examples on how AI can be applied Security and Compliance:

  • Identifies actionable insights from data using Data Analytics
  • Identifies impending failures and threats before they may occur
  • Flags suboptimal operational and maintenance workflows
  • Automates repetitive security & compliance tasks
  • Enhances human analysis

Artificial intelligence in corporate governance can offer companies next-level problem solving, market predictions, and risk management procedures far more advanced than legacy practices. A good place for organizations to start is by strategizing AI Governance and Policies in order to provide a clear direction to the user community on Do’s and Don’ts of using AI in the organization.

AI Governance Challenges:

  1. Can the AI system be designed and operated to reflect human values such as fairness, accountability, and transparency?
  2. Can we ensure the safety and certification of AI technology so that the use of AI is not harmful?
  3. What are the privacy implications when AI is powered by the data and it is able to make its own decisions?
  4. What are the implications for jobs by adopting AI?

The Board of Directors should find answers to the following questions related to opportunities in AI and associated risks. This could also be used to define the AI Governance approach for the organization too.

  • Can AI comply with current applicable legal and regulatory requirements to the organization?
  • Can the AI technologies meet the corporate ethics rules?
  • Have we considered how AI can transform our products or services and which aspects of our business could benefit from increased automation or machine learning?
  • How might AI fit with other emerging technologies we are investing in?
  • Do we have the computing power and infrastructure to support the use of AI?
  • Do we have the digital skills and talent to move forward?
  • How will we gain the trust of our stakeholders if we use AI?
  • Have we thought about how we will use data collected by AI?
  • Have we considered cyber risks and data privacy issues?

Well-structured corporate policies can provide valuable benefits:

  • Allowing for the corporate-wide articulation of ethical and legal principles to guide decisions about acceptable use of AI
  • Aligning decision-making with articulated principles
  • Improving legal compliance
  • Increasing transparency and information sharing across the organization
  • Ensuring consistency in approach to decision-making and compliance

Next week in Part II we will deep dive into the contents of AI Policies. We have sourced information from the articles and interviews published by PWC, Corporate Compliance, Gartner and “Leveraging Artificial Intelligence and Machine Learning for Security and Compliance” from Priti Ved.

Related posts

Prevention, Detection, and Recovery from Cyberattacks Part II

2 Mins read
The second blog post in the series of Prevention, Detection, and Recovery from Cyberattacks. The global survey conducted by Ponemon Institute and…

Prevention, Detection, and Recovery from Cyberattacks Part I

3 Mins read
During the team discussion about next-gen tools and techniques for prevention, detection, and recovery from cyberattacks, we started looking at some of…

Artificial Intelligence Use Cases & Data Part III

2 Mins read
In Part-I we discussed advantages, security, and compliance consideration, challenges, and governance aspects of AI. In part-II we focused on AI policies….

Leave a Reply

Your email address will not be published. Required fields are marked *