3 Trustworthy AI



Trustworthy AI
We help deploying reliable AI that is under human supervision, and algorithms that will not turn against your organization, or engage in discriminative, unlawful, or counterproductive behavior. We automate data and metadata management, documentation, verification, because computers are much better than humans in these boring tasks; humans must increasingly focus on oversight of too much data.
Human agency and oversight AI systems should empower human beings, allowing them to make informed decisions and fostering their fundamental rights. At the same time, proper oversight mechanisms need to be ensured, which can be achieved through human-in-the-loop, human-on-the-loop, and human-in-command approaches
Technical Robustness and safety AI systems need to be resilient and secure. They need to be safe, ensuring a fall back plan in case something goes wrong, as well as being accurate, reliable and reproducible. That is the only way to ensure that also unintentional harm can be minimized and prevented.
Privacy and data governance besides ensuring full respect for privacy and data protection, adequate data governance mechanisms must also be ensured, taking into account the quality and integrity of the data, and ensuring legitimised access to data.
Transparency the data, system and AI business models should be transparent. Traceability mechanisms can help achieving this. Moreover, AI systems and their decisions should be explained in a manner adapted to the stakeholder concerned. Humans need to be aware that they are interacting with an AI system, and must be informed of the system’s capabilities and limitations.
Diversity, non-discrimination and fairness Unfair bias must be avoided, as it could have multiple negative implications, from the marginalization of vulnerable groups to the exacerbation of prejudice and discrimination. Fostering diversity, AI systems should be accessible to all, regardless of any disability, and involve relevant stakeholders throughout their entire life circle.
Societal and environmental well-being AI systems should benefit all human beings, including future generations. They should consider the environment, including other living beings, and their social and societal impact should be carefully considered.
Accountability Mechanisms should be put in place to ensure responsibility and accountability for AI systems and their outcomes.