WS 7: Human vs. algorithmic bias – is unbiased decision-making even a thing?
Rapporteur: Katharina Hone, Geneva Internet Platform
- Algorithmic bias is a particular concern regarding sensitive decisions with human rights implications. Ultimately, the outcomes of machine learning should be seen as only one input into decisions eventually taken by humans.
- A broad understanding of bias is warranted to address discrimination and harm. Bias can materialise at all steps of developing and using a particular AI system. This includes decisions about the algorithms, data, and the context in which the system is used. There are also mechanisms to make humans and machines work together better for better decisions.
- Policies need to mitigate risks of algorithmic decision-making. Constraints, safety mechanisms, audit mechanisms, and algorithmic recourse all need to be in place. In addition, it is crucial, as a first step, to work towards greater transparency and explainability of AI systems involved in decision-making. Databases that list the AI systems and data in use should be considered, as well as bans on the use of certain AI systems with high risk and high harm.
- A number of technological companies have self-regulation mechanisms in place at various levels. Self-regulation of the private sector is important but ultimately not enough. Various regulatory efforts need to complement each other and greater cooperation between various stakeholders is needed to create synergies.
- Equality and fairness are values that have a strong cultural connotation. They are important principles to address bias, yet it is not easy to find an intercultural agreement on some aspects of these principles. Addressing algorithmic bias also needs to include discussion on what kind of society we want to live in in the future.
Recent Comments on this Site
27th February 2023 at 4:40 am
room for statistical innovation with quantum, robots and mind reading applications now in development.
See in context
27th February 2023 at 4:39 am
Green ehealth aps
See in context
27th February 2023 at 4:38 am
New theme of Digital Health is required
See in context
27th February 2023 at 4:37 am
collaboration of techiques / know-how, can enhance medical aps
See in context
27th February 2023 at 4:36 am
very important. brainwave techs, Quantum, VR, how algorithms work for a health ap etc. Naive users must not be made use of. Consent is key, What is a reasonable person ?
See in context
27th February 2023 at 4:34 am
Medical aps and ethics. Ethics for brain wave ehealth applications operation. VR ethics.
See in context
27th February 2023 at 4:33 am
New era of brain waves for manipulating the applications such as robots or VR. Ethics is important.
See in context
27th February 2023 at 4:32 am
Important for medical internet of things and ehealth for SDG 3
See in context
27th February 2023 at 4:31 am
Transparency of data sources and algorithms. Building of trust and human oversight. Zero failures for healthcare. Due diligence and audits that are timely. Getting rid of errors and old non relevant data.
See in context
27th February 2023 at 4:29 am
critical for medical information
See in context