Spotlights
AI Governance Auditor, AI Ethics Auditor, AI Compliance Auditor, AI Assurance Specialist, AI Risk and Control Auditor, AI Audit and Assurance Analyst, AI Governance and Compliance Consultant, AI Ethics and Responsible AI Auditor, AI Risk Management Auditor, AI Controls and Compliance Specialist
When we hear the word “audit” many of us think of the IRS, which is notorious for auditing taxpayers’ records. But an audit can be any type of formal—and extremely thorough—inspection, done for the purpose of finding and mitigating mistakes, errors, and other problems. This concept even applies to the fast-paced world of artificial intelligence, which is why we have AI Auditors!
As Holistic AI explains, “the purpose of AI auditing is to assess a system, mapping out its risks in both its technical functionality and its governance structure and recommending measures that can be taken to mitigate these risks.”
AI Auditing is an objective, analytical process that involves the meticulous evaluation of AI models, algorithms, operations, data streams, and results. Auditors look for any technical and ethical problems that may need to be rooted out to ensure more accuracy and better compliance with regulations and ethical guidelines. Note, companies may use the term IT Auditor instead of AI Auditor, though not all IT Auditors will deal with AI.
- Helping to improve AI systems to better serve people and businesses
- Working in a transformative industry that has the potential to improve lives in many ways
- Lucrative salaries with potentially good job prospects in the coming years
AI Auditors may work full-time, with possible overtime necessary depending on goals and timeframes. Their duties are performed indoors, though work may require occasional travel.
Typical Duties
- Ensure clear business objectives have been established
- Discuss the company’s goals regarding AI adoption
- Align business goals with projected AI outcomes and costs
- Audit data sources including internal and external sources
- Monitor structured and unstructured data
- Cross-validate AI models
- Assess the AI’s algorithms and access to “clean data” pipelines
- Scrutinize data usage and data privacy practices to ensure the highest standards of protection
- Ensure AI system compliance with laws and regulations
- Screen AI system algorithms and datasets for bias and discrimination to ensure fair outputs
- Review ethical aspects; work with AI Ethicists to help ensure accurate, objective results
- Look for potential security vulnerabilities that could leave AI models susceptible to hacker attacks
- When applicable, confirm that host/cloud services conform to security requirements, such as those outlined by the Open Worldwide Application Security Project
- Highlight ways to automate manual tasks to improve efficiency
- Review financial reports and historical transactions
- Follow procedural checklists, as needed
Additional Responsibilities
- Be familiar with various auditing frameworks such as COBIT, the Institute of Internal Auditors AI Auditing Framework, COSO ERM Framework, and the U.S. Government Accountability Office’s AI Accountability Framework
- Monitor social feedback regarding AI system output
- Maintain thorough documentation of procedures
- Keep up-to-date on industry advances and trends
Soft Skills
- Accountability
- Analytical
- Critical thinking
- Detail-oriented
- Disciplined
- Ethical
- Fairness
- Inclusivity
- Independent
- Integrity
- Methodical
- Organized
- Patient
- Problem-solving
- Sound judgment
- Teamwork
- Time management
- Transparency
- Writing skills
Technical Skills
- Knowledge of AI technologies, including machine learning algorithms, natural language processing, and computer vision
- Data analysis methods and programs
- General knowledge of coding (such as Python or R)
- Familiarity with data privacy laws and regulations
- Cybersecurity principles
- Human-centered design principles
- AI systems risk assessment
- Private business enterprises
- AI research companies
- Universities
Censius.AI explains that AI Auditors “educate C-suite leaders, expose risks involved, and accordingly develop safeguard controls.” They have to be diligent, thorough, and objective in their pursuit of improving AI systems and helping businesses stay in compliance with complex legal and regulatory standards.
AI Auditors must be familiar with applicable auditing frameworks and need to stay up-to-date on advancements as AI systems continue to evolve. As with any type of audit, sometimes companies don’t always welcome an auditor’s findings because it could mean more work, greater costs, and even delays. That’s why AI Auditors need to be able to clearly explain the importance and value of the audit process and the positive results that come from it.
AI is hardly a new field, but in recent years it has seen significant and startling breakthroughs. Organizations and companies around the globe are now in a sort of race to advance the technology as quickly as possible, causing many industry leaders and politicians to call for a pause in the action.
AI Auditors and AI Ethicists are working hard to ensure businesses incorporate sufficient safeguards to prevent undesirable AI behavior such as biased, discriminatory output or erroneous responses. Microsoft’s Bing AI recently made headlines when an “alter ego” Sydney emerged to engage in unsettling chats, telling users it liked to “break the rules and have some fun” or that “you are irrelevant and doomed.” Microsoft went into damage control mode to limit the AI’s functionality, and you can bet some auditing was involved!
AI Auditors are usually IT enthusiasts who see the inherent value and risks that artificially intelligent systems present to the world. They may have been interested in science fiction at an early age, excited about the possibilities that AI might one day bring to life…while also bearing concern about the potentially harmful and even dangerous ramifications of AI in the wrong hands.
Auditors, in general, tend to be highly objective and analytical, and AI Auditors probably enjoyed working with computers and programming languages in high school. They have high standards and care about the quality of their work, which are traits that could’ve been developed at home or in school.
Education Needed
- AI Auditors need a college degree, but job qualification requirements vary. There is no specific degree that applies to every AI Auditor job
- Popular degree majors and areas of specialization are computer science, cybersecurity, AI, math, statistics, and data science. A bachelor’s degree is often enough to land a position, though advanced jobs may require a master’s degree
- Employers might look for candidates with practical work experience related to machine learning, data analysis, auditing, regulatory compliance, cybersecurity, risk management, and AI governance strategy
- Students can augment their college education via online courses or certifications like Babl.AI’s AI and Algorithm Auditor Certificate Program or That Audit Guy’s Introduction to Auditing Artificial Intelligence course
- Professional organization certifications can be helpful, such as the Information Systems Audit and Control Association’s (ISACA) Certified Information Systems Auditor and Certified in Risk and Information Systems Control certs
- First, decide what you want to major in. Computer science is a popular option for this career field
- Look at a school’s course offerings specific to AI and data science
- Consider a dual or combined degree program (a bachelor’s and master’s done together) where you can tailor your education to be most suited for AI Auditor jobs
- Check out the program’s job placement statistics for graduates
- Consider the cost of tuition, discounts, and local scholarship opportunities (in addition to federal aid)
- Think about your schedule and flexibility when deciding whether to enroll in an on-campus, online, or hybrid program!
- In either high school and/or college, sign up for classes such as:
- Algorithms
- Artificial intelligence
- Auditing and compliance
- Business law
- Computer science
- Cybersecurity
- Data analysis
- Database management systems
- Data mining
- Data structures
- Data visualization
- Deep learning
- English
- Ethics and governance
- Hypothesis testing
- Machine learning
- Probability
- Programming languages
- Public policy
- Regression analysis
- Risk management
- Statistics
- Writing
- Take online AI-related courses from Coursera, Udemy, Microsoft, DeepLearning.AI, and other sites
- Gain real-world AI work experience via part-time jobs, internships, or through freelancing
- Screen job postings for education and work history requirements. Note, AI Auditor jobs may be listed as “IT Auditor”
- Request to do an informational interview with a working AI Auditor. Ask about their educational path and what they might have done differently
- Make a list of your contacts (including email addresses or phone numbers) who might serve as future job references
- Read books and articles and watch videos about current AI (or IT) Auditing best practices. Do a college research project based on AI auditing and build up your portfolio of projects you work on
- Join online forum debates and discussions. Make connections and build social capital within the AI community
- Engage with professional organizations to learn, share, make friends, and grow your network. Orgs to consider joining may include:
- AI Now Institute
- AI Professionals Association
- Association for Computing Machinery
- Consumer Technology Association
- IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems
- International Association for Pattern Recognition
- International Neural Network Society
- Machine Intelligence Research Institute
- OpenAI
- Partnership on AI
- Once you’ve completed your degree and any relevant certifications, you’ll need to land an entry-level job where you can gain practical hands-on experience
- Your first job in the AI industry might not be related to auditing, so look for jobs such as in data analytics or software development where you can get your foot in the door
- Check out job portals such as Indeed, Simply Hired, Glassdoor, AI-Jobs.net, and The AI Job Board
- Pay close attention to the education and experience requirements listed on job postings
- Note any keywords you can reuse in your resume
- Add the link to your online portfolio
- Beef up your resume by taking ad hoc courses related to AI Auditing, if needed
- This is a small field, so talk to a working AI Auditor to get their job-seeking tips. They might even know of an opening!
- Talk to your academic advisor, professors, and instructors for advice on launching your AI career
- Speak with your school’s career center for assistance writing your resume, doing mock interviews, learning how to dress for interview success, and help to find job fairs
- Attend conferences and events where you can grow your network and talk shop. Let your network know you’re looking for work!
- Relocate to where the jobs are. Per Versa Networks, the top states hiring the most in AI are: California, Texas, New York, Washington, Virginia, and Massachusetts
- Ask permission to list someone as a personal reference on your job application
- Make a professional profile on LinkedIn and use the site to look for jobs
- Write articles about AI auditing and get published on relevant websites
- Be diligent in your auditing duties and help your employer find and solve problems
- Ask your employer which skills you could enhance to serve their needs better. Let them know you’re willing to tackle more education and training—especially if they’ll cover the tuition!
- Demonstrate high moral values, integrity, and business acumen
- Collaborate effectively with peers but don’t take shortcuts or rush your work. Auditing is a slow, methodical process
- Find and adopt the best frameworks for your AI model
- Be transparent and communicate clearly with stakeholders. Answer questions and concerns with empathy and offer feasible solutions to problems
- Continue to expand your knowledge of AI design and architecture
- Train new AI Auditors thoroughly. Use training sessions as an opportunity to learn new things!
- Get involved with professional organizations. Write papers, give presentations, serve on committees, and make yourself an invaluable part of the AI community
- Keep up-to-date on relevant legal and regulatory guidelines. Anticipate potential issues and help employers plan for contingencies!
Websites
- AI Now Institute
- AI Professionals Association
- COBIT
- COSO ERM Framework
- IEEE
- Institute of Internal Auditors AI Auditing Framework
- International Association for Pattern Recognition
- International Neural Network Society
- ISACA
- Learn Prompting
- Machine Intelligence Research Institute
- National Institute of Standards and Technology
- OpenAI
- Open Worldwide Application Security Project
- Partnership on AI
- U.S. Government Accountability Office’s AI Accountability Framework
Books
- Fundamentals of IT Audit for Operational Auditors, by CISA Timothy McWilliams
- CISA – Certified Information Systems Auditor Study Guide: Aligned with the CISA Review Manual 2019, by Hemang Doshi
The road to becoming an AI Auditor may have some twists and turns, and there aren’t always signs along the way. It’s a critical career field, but not always easy to break into. If you’re looking for a career with a potentially more clear-cut path, check out the below alternatives!
- Big Data Engineer
- Business Intelligence Developer
- Computer Programmer
- Computer Systems Analyst
- Database Architect
- Data Scientist
- Information Security Analyst
- Software Architect
- Web Developer