Algorithmic Audits
Validate your algorithm with an external audit
BENEFITS OF AN ALGORITHMIC AUDIT
Seduced with the promise of AI-powered algorithms, many companies have embedded at least one AI in their business processes or started building a strategy to incorporate AI into their business.
However, as AI usage grows, so do the risks an organization can be liable for when an algorithm malfunctions. Business blunders manifesting on a large scale, in a very short period of time will happen. Even worse, we’ve seen it happen. The most important point is how to remediate it.
You know you have many sources of data points and that AI-powered technology can help you capture and extract value from that data in ways that will give you a competitive edge.
But you’re in the dark about where you’re vulnerable. We can help.
RISK MITIGATION:
UNDERSTAND YOUR LEGAL RISKS
When an algorithm renders a wrong decision and the business unknowingly executes on that decision, legal disputes over responsibilities might arise between AI technology providers and companies.
We help you understand your risks and answer the question: What could go wrong?
ADDRESS ALGORITHMIC BIAS
Algorithmic bias is not just about race, gender and age discrimination.
AI-powered algorithms can identify the wrong patient, target market, hire, investment, pandemic, X factor, etc. Biases are almost always unknown unknowns.
An algorithmic audit identifies, addresses and corrects algorithmic bias so that you can act on informed and vetted AI-powered business recommendations.
UP-TO-DATE ALGORITHMS
Most algorithmic systems need to be trained on lots of historical data.
As a result, AI-powered technologies are often based on data drawn from past behavior and aren’t prepared to deal with massive shifts in behavior because of a horrible pandemic or financial crisis.
So when the present suddenly stops looking like the recent past, algorithms end up performing much worse than expected. Events without historical data, understanding context is even more crucial.
Algorithmic audits can help.
ALGORITHMIC AUDITS:
CLIENTS
I can certainly vouch for the value of an Eticas audit
Ollie Smith, Alpha Health
AN ALGORITHMIC AUDIT PROVES
Diversity
Represents the population.
Inclusiveness
Engages with all individuals and doesn’t automatically target a protected group.
Accountability
Provides an unambiguous rationale for all decisions made.
Reliability
Performs reliably and safely.
Oversight
Continuously manages risk – pandemic, sudden financial crisis, or a rare outlier event.
Recent Blog Posts
La “ley rider”, un pequeño gran paso para la regulación de la IA en entornos laborales
Algorithms, Auditoría de algoritmos
La “ley rider”, un pequeño gran paso para la regulación de la IA en entornos laborales
El Gobierno ha aprobado la popularmente conocida como ‘ley rider’, una normativa pensada para que los repartidores de plataformas como Glovo, Deliveroo y Uber Eats dejen de ser autónomos. Pero, a la vez, se trata de una ley que va mucho más allá de dicho sector. Y es que la nueva ley convierte a España […]
Privacy by design and the digital border
Privacy by design and the digital border
Data governance should not only be considered regarding legal requirements for the system at hand and corresponding responsibilities distribution but from the managerial side, focusing on end users’ role in administering sensitive data. All in all, there is a significant margin for improvement regarding privacy by design, and Eticas will continue pushing in this direction. […]
Introducing the Guide to Algorithmic Auditing
Algorithms, Auditoría de algoritmos
Introducing the Guide to Algorithmic Auditing
Addressed to companies, public organisms and citizens, this guide to audit algorithms offers a general and replicable methodology. Big data, especially the one based on Artificial Intelligence (AI) that use personal information, has an enormous effect on our daily lives. On a personal scale but also on a social, economic and legal level. And the […]