Towards algorithm auditing: managing legal, ethical and technological risks of AI, ML and associated algorithms
Contact us if these videos are not relevant.
Contact us if these videos are not relevant.
View abstract on PubMed
Summary
This summary is machine-generated.Algorithm audits are essential for businesses to ensure AI systems are legal, ethical, and safe. This new field of Auditing and Assurance of Algorithms will professionalize AI and machine learning development.
Area Of Science
- Computer Science
- Ethics in AI
- Regulatory Compliance
Background
- Businesses increasingly rely on algorithms, facing risks of financial and reputational damage from biased or unsafe AI.
- High-profile incidents highlight the need for accountability in AI, including issues with photo classification, chatbots, and recruiting tools.
Purpose Of The Study
- To survey key areas for performing auditing and assurance of algorithms.
- To instigate debate and establish a framework for a new industry focused on Auditing and Assurance of Algorithms.
Main Methods
- Literature review of existing AI ethics and governance challenges.
- Conceptual framework development for algorithm auditing and assurance.
- Stakeholder analysis including policymakers, industry practitioners, and developers.
Main Results
- Identified the necessity of formal assurance for algorithms to ensure legality, ethicality, and safety.
- Proposed the establishment of an Auditing and Assurance of Algorithms industry, akin to financial auditing.
- Anticipated the development of auditing levels and frameworks to guide governance and compliance.
Conclusions
- Algorithm audits are crucial for mitigating risks associated with ubiquitous AI adoption.
- A new professionalized industry for Auditing and Assurance of Algorithms is envisaged.
- The proposed framework will inform governance and regulatory compliance for AI systems.
Contact us if these videos are not relevant.
Contact us if these videos are not relevant.
Related Concept Videos
A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
Cost Containment
Payment for healthcare services has historically promoted adoption of costly and often unnecessary or inefficient...
Today, scientists agree that good research is ethical in nature and is guided by a basic respect for human dignity and safety. However, this has not always been the case. Modern researchers must demonstrate that the research they perform is ethically sound.
Research Involving Human Participants
Any experiment involving the participation of human subjects is governed by extensive, strict guidelines designed to ensure that the experiment does not result in harm. Any research institution that...
Heuristics are problem-solving strategies that use mental shortcuts to simplify decision-making. Unlike algorithms, which must be followed precisely to achieve a correct result, heuristics offer a general problem-solving framework. They save time and energy but can sometimes lead to less rational decisions.
People often rely on heuristics when faced with an overload of information, limited time, low importance of the decision, limited information, or when a heuristic readily comes to mind. For...
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...