Artificial Intelligence audits are necessary to ensure safety and responsibility in the use of AI technologies. Regulators and laws are beginning to require AI audits to assess potential risks and ensure technologies are being used ethically and safely.
These audits are not yet very common, but they will be necessary to assess the system and advise on how to manage the identified risks, all objectively.
The idea is that we can establish an AI risk management framework at the enterprise level to ensure a sustainable and secure implementation of the technology in the long term. Or put another way, so that AI always acts to benefit humanity as a whole, keeping it under control.
Those responsible for ChatGPT have already spoken on the subject in TIME magazine, making it clear that they are not only beneficial, they must be mandatory.
How an Artificial Intelligence audit works
An artificial intelligence audit is a systematic process of review and evaluation of artificial intelligence systems and processes in order to guarantee their proper functioning, ethics, security and compliance with standards and regulations.
These audits can be used to verify the accuracy, fairness and robustness of the models, to evaluate how sensitive and personal data are handled and protected, to verify if the AI models have biases or perpetuate discrimination, to evaluate the security of the systems and protection against possible attacks or vulnerabilities, to verify if AI systems and processes comply with applicable standards and regulations…
To do all this, which is not a small thing, it is necessary to include a combination of technical tests, data evaluations, interviews with experts and documentation review.
Possible problems found in an Artificial Intelligence audit
The most common problems found in an audit of this type are related to security and discrimination. If a model trains on random photos from the Internet, it’s very possible that she’s prejudiced about race and gender, since content of this type abounds on the web of networks.
Other problems that can be found would be:
– The model is not making accurate predictions, which can have negative consequences in a wide variety of applications, such as healthcare, finance, criminal justice, etc.
– The model is a “black drawer”, where it is difficult to understand how decisions are made, which can create mistrust and a lack of responsibility.
– The model is not properly regulated, which may result in the misuse of personal information and the privacy of users.
As we continue to live with Artificial Intelligence models, we will see more details about how these audits should be and how they should be prepared.
What to do before carrying out an Artificial Intelligence audit in a company
Auditors must prepare very well when carrying out an audit of this type, since each company has a completely different way of working, so audits must be highly personalized.
It is important to note that the Artificial Intelligence audit must be carried out by a team with experience and knowledge in the area of AI, and that is independent of the company being audited.
Some points that should be worked on before starting:
– Know the objectives and requirements of the company: It is important to understand the needs and expectations of the company before beginning the audit.
– Review relevant documents: Review company policy and procedure documents as well as AI implementation records.
– Identify key teams: Identify the key teams and individuals who have responsibilities for the implementation and use of AI in the company.
– conduct interviews: Conduct interviews with key people and get their perspective on AI implementation and practices.
– evaluate performance: Assess the performance and effectiveness of AI in the enterprise, including accuracy, consistency, and security.
– Identify areas for improvement: identify areas where AI can be improved and make recommendations to fix problems found during the audit.
– Prepare a detailed report: prepare a detailed report that includes the results of the audit, the areas for improvement identified and the recommendations for the company.
A sector that will grow a lot in the coming years.