Algorithmic transparency is the principle that the factors that influence the decisions made by algorithms should be visible, or transparent, to the people who use, regulate, and are affected by systems that employ those algorithms. Although the phrase was coined in 2016 by Nicholas Diakopoulos and Michael Koliska about the role of algorithms in deciding the content of digital journalism services,[1] the underlying principle dates back to the 1970s and the rise of automated systems for scoring consumer credit.
The phrases "algorithmic transparency" and "algorithmic accountability"[2] are sometimes used interchangeably – especially since they were coined by the same people – but they have subtly different meanings. Specifically, "algorithmic transparency" states that the inputs to the algorithm and the algorithm's use itself must be known, but they need not be fair. "Algorithmic accountability" implies that the organizations that use algorithms must be accountable for the decisions made by those algorithms, even though the decisions are being made by a machine, and not by a human being.[3]
Current research around algorithmic transparency interested in both societal effects of accessing remote services running algorithms.,[4] as well as mathematical and computer science approaches that can be used to achieve algorithmic transparency[5] In the United States, the Federal Trade Commission's Bureau of Consumer Protection studies how algorithms are used by consumers by conducting its own research on algorithmic transparency and by funding external research.[6] In the European Union, the data protection laws that came into effect in May 2018 include a "right to explanation" of decisions made by algorithms, though it is unclear what this means.[7] Furthermore, the European Union founded The European Center for Algoritmic Transparency (ECAT).[8]
^Nicholas Diakopoulos & Michael Koliska (2016): Algorithmic Transparency in the News Media, Digital Journalism, doi:10.1080/21670811.2016.1208053
^Diakopoulos, Nicholas (2015). "Algorithmic Accountability: Journalistic Investigation of Computational Power Structures". Digital Journalism. 3 (3): 398–415. doi:10.1080/21670811.2014.976411. S2CID 42357142.
^Dickey, Megan Rose (30 April 2017). "Algorithmic Accountability". TechCrunch. Retrieved 4 September 2017.
^"Workshop on Data and Algorithmic Transparency". 2015. Retrieved 4 January 2017.
^"Fairness, Accountability, and Transparency in Machine Learning". 2015. Retrieved 29 May 2017.
^Noyes, Katherine (9 April 2015). "The FTC is worried about algorithmic transparency, and you should be too". PCWorld. Retrieved 4 September 2017.
^"False Testimony" (PDF). Nature. 557 (7707): 612. 31 May 2018.
^"About - European Commission".
and 25 Related for: Algorithmic transparency information
Algorithmictransparency is the principle that the factors that influence the decisions made by algorithms should be visible, or transparent, to the people...
the 1970s and algorithmic management is becoming increasingly widespread across a wide range of industries. The concept of algorithmic management can...
The European Centre for AlgorithmicTransparency (ECAT) provides scientific and technical expertise to support the enforcement of the Digital Services...
Government by algorithm (also known as algorithmic regulation, regulation by algorithms, algorithmic governance, algocratic governance, algorithmic legal order...
Regulation of algorithms, or algorithmic regulation, is the creation of laws, rules and public sector policies for promotion and regulation of algorithms, particularly...
of transparency is often disguised as a result of algorithmic complexity, shielding companies from disclosing or investigating its own algorithmic processes...
of AI in hiring remain a subject of debate, with concerns about algorithmictransparency, accountability, and the need for ongoing oversight to ensure fair...
Certificate Transparency (CT) is an Internet security standard for monitoring and auditing the issuance of digital certificates. The security of HTTPS...
and on the way advertisers target users. The European Centre for AlgorithmicTransparency was created to aid the enforcement of this. A 16 November 2021...
than with a general standard explanation. Algorithmictransparency – study on the transparency of algorithmsPages displaying wikidata descriptions as a...
accountability in AI, including algorithmic bias, algorithmic decision-making, algorithmic governance, and algorithmic auditing. Additionally there is...
governing algorithmic decision-making and grapple with new challenges presented by the rise of algorithmic power in terms of transparency, fairness,...
defining transparency within the context of algorithmic accountability remains a problem. For example, providing the source code of algorithms may not...
most often connected to ideas of government transparency, participation and accountability. Transparency is defined as the visibility and inferability...
and research exercises. The topics of the programmes range from algorithmictransparency to exploring the implications of AI for democracy. AI: Futures...
In analytic philosophy and computer science, referential transparency and referential opacity are properties of linguistic constructions, and by extension...
Algorithmic radicalization is the concept that recommender algorithms on popular social media sites such as YouTube and Facebook drive users toward progressively...
RGBA colors), grayscale images (with or without an alpha channel for transparency), and full-color non-palette-based RGB or RGBA images. The PNG working...
ECAT may refer to European Centre for AlgorithmicTransparency (part of the European Commission) Emergency Committee for American Trade Escambia County...
paradigms: data model and algorithmic model, wherein "algorithmic model" means more or less the machine learning algorithms like Random Forest. Some statisticians...
image with a background to create the appearance of partial or full transparency. It is often useful to render picture elements (pixels) in separate passes...
case of algorithmic governance is not exceptional. Regulated parties might even employ adversarial machine learning in order to fool algorithmic models...
affect whether or not people accept algorithmic recommendations. For example, one study found that trust in an algorithmic financial advisor was lower among...
on algorithmic bias, AI accountability, and algorithmic auditing. Raji has previously worked with Joy Buolamwini, Timnit Gebru, and the Algorithmic Justice...
forbes.com. Retrieved March 19, 2022. "Algorithmic Justice League - Unmasking AI harms and biases". Algorithmic Justice League - Unmasking AI harms and...
Global Information