The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index; 6 of the 22 sources its claims cite were checked for support.
Bias in computer systems
Open accessAbstract
From an analysis of actual cases, three categories of bias in computer systems have been developed: preexisting, technical, and emergent. Preexisting bias has its roots in social institutions, practices, and attitudes. Technical bias arises from technical constraints of considerations. Emergent bias arises in a context of use. Although others have pointed to bias inparticular computer systems and have noted the general problem, we know of no comparable work that examines this phenomenon comprehensively and which offers a framework for understanding and remedying it. We conclude by suggesting that freedom from bias should by counted amoung the select set of criteria—including reliability, accuracy, and efficiency—according to which the quality of systems in use in society should be judged.
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Claims the paper makes
6 of 22 cited sources checked · 4 supported · 0 flagged · accuracy not yet measured
Every source the paper cites for this claim was checked and supports it.
In the paper
“As specified in Section 50-(9) of the British Nationality Act itself and imple-mented in BNAP,”
§ Bias in Computer Systems > 3.3 The British Nationality Act Program (BNAP)
What the sources say
- Supportedcites Sergot et al. 1986 source
The “Formalization by Trial and Error” passage states the same distinction: a man is the father only of his legitimate children, while a woman is the mother of all her children. It also says incorporating that provision requires an adjustment to the existing rules, supporting the claim that it was implemented in the logic program. (LLM, conf=0.94)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Supported
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“At this point, it was discovered that the original Admissions Algorithm placed married couples at a disadvantage in achieving an optimal placement as compared with their single peers [Roth 1984;1990].”
What the sources say
- Partly supportedcites Roth 1984 sourceExperimental — accuracy not yet measured
Section IV, “Contemporary Issues” (page not supplied), says the couples algorithm used until 1983 could not accept preferences over pairs of positions and could produce outcomes unstable with respect to couples. That supports a disadvantage for couples, but the paper does not establish that couples achieved less optimal placements than single applicants. (LLM, conf=0.84)
- Not checked — no full text of the sourcecites Roth 1990 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Partly supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“In this manner the MLSA gives processing attention to all processes as quickly as possible that are beginning a new command.”
§ Bias in Computer Systems > 3.2 A Multilevel Scheduling Algorithm (MLSA)
What the sources say
- Supportedcites Corbato et al. 1962 source
The “A Multi-Level Scheduling Algorithm” section says programs entering the system are placed in priority queues and that scheduling begins with the lowest occupied level, switching to a newly occupied lower level. The IBM 7090 system section also says the supervisor gives top priority to initiating waiting commands. Together, these passages support the paraphrase about prompt attention to processes beginning a command. (LLM, conf=0.88)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Supported
Every source the paper cites for this claim was checked and supports it.
In the paper
“At the time of the BNAP's initial implementation (1983) no mechanism was built into the program to incorporate relevant case law as it came into being [Sergot et al. 1986].”
§ Bias in Computer Systems > 3.3 The British Nationality Act Program (BNAP)
What the sources say
- Supportedcites Sergot et al. 1986 source
The introduction says the Act was free of case law when the original implementation began in summer 1983. It also says the authors deliberately avoided incorporating rules derived from previous cases, leaving treatment of case law for further investigation. These passages support the claim that the initial program had no built-in means of incorporating emerging case law. (LLM, conf=0.88)
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Supported
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The Admissions Algorithm does not take into account geographic distribution when determining a match, considering only the ranked preferences of hospitals and students.”
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim have been checked yet.
In the paper
“Although others have pointed to bias in particular computer systems and have noted the general problem, we know of no comparable work that examines this phenomenon comprehensively and which offers a framework for understanding and remedying it.”
- Also stated in: § INTRODUCTION · hedged
“Although others have pointed to bias in particular computer systems and have noted the general problem [Johnson and Mulvey 1993;Moor 1985], we know of no comparable work that focuses exclusively on this phenomenon and examines it comprehensively.”
§ Bias in Computer Systems > Abstract
What the sources say
- Not matchedcites Johnson and Mulvey 1993
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked — no full text of the sourcecites Moor 1985 source
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes? Based: unclear- Also stated in: § INTRODUCTION · hedged
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“From an analysis of actual cases, three categories of bias in computer systems have been developed: preexisting, technical, and emergent.”
- Also stated in: § INTRODUCTION · plain
“From an analysis of actual computer systems, we have developed three categories: preexisting bias, technical bias, and emergent bias.”
- Also stated in: § 2. FRAMEWORK FOR ANALYZING BIAS IN COMPUTER SYSTEMS · plain
“The framework that emerged from this methodology is comprised of three overarching categories-preexisting bias, technical bias, and emergent bias.”
§ Bias in Computer Systems > Abstract
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: The 17 computer systems examined are representative enough to generalize the framework to computer systems generally.
- Also stated in: § INTRODUCTION · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Emergent bias arises in a context of use.”
- Also stated in: § 2.3 Emergent Bias · plain
“emergent bias arises only in a context of use.”
§ Bias in Computer Systems > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Also stated in: § 2.3 Emergent Bias · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, in terms of overall service from the processor, these individuals with long-running programs are systematically disadvantaged.”
§ Bias in Computer Systems > 3.2 A Multilevel Scheduling Algorithm (MLSA)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus the British Nationality Act is biased against the illegitimate descendants of British men.”
§ Bias in Computer Systems > 3.3 The British Nationality Act Program (BNAP)
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
- Probably not a substantial claim. 18
- It may state two separate claims as one. 15
The cited sources support only part of this claim — read each source’s verdict below.
In the paper
“For in the same text the authors also state (as noted above) that their goal is to translate the British Nationality Act so that”
§ Bias in Computer Systems > 5. CONCLUSION
What the sources say
- Partly supportedcites Sergot et al. 1986 sourceExperimental — accuracy not yet measured
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
- Partly supported
The sources with a verdict support this claim; the rest weren’t checked yet, have no full text we could read, or their verdicts aren’t rated yet.
In the paper
“One charges that the Admissions Algorithm systematically favors hospital programs over medical students in cases of conflict [Graettinger and Peranson 1981b;Roth 1984;Sudarshan and Zisook 1981;Williams et al. 1981].”
§ Bias in Computer Systems > 3.1 The National Resident Match Program (NRMP)
What the sources say
- Not matchedcites Graettinger and Peranson 1981b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Supportedcites Roth 1984 source
Section III (Theoretical Analysis; page unavailable) states that the NRMP algorithm produces the best stable outcome for hospitals and the worst for students when preferences are submitted as strict rank-order lists. Section IV (Contemporary Issues; page unavailable) also identifies whether the algorithm unfairly favors hospitals as an issue that had been raised, while noting a qualification when participants may be indifferent between matches. (LLM, conf=0.92)
- Not checked — no full text of the sourcecites Williams et al. 1981 source
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✗ Asserted: fails✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The authors may not put it forward as true. The paper’s conclusions may not depend on it.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Technical bias arises from technical constraints or considerations.”
- Also stated in: § 2.1 Preexisting Bias · plain
“Technical bias arises from technical constraints or technical considerations.”
§ Bias in Computer Systems > Abstract
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Also stated in: § 2.1 Preexisting Bias · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Preexisting bias has its roots in social institutions, practices, and attitudes.”
- Also stated in: § INTRODUCTION · plain
“Preexisting bias has its roots in social institutions, practices, and attitudes.”
§ Bias in Computer Systems > Abstract
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
- Also stated in: § INTRODUCTION · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In this case, we ourselves would shy away from viewing this as a bias in the system because we think this discrimination can be defended as having a reasonable basis.Namely, the discrimination reflects the preferences of match participants, and it is reasonable in our view for employment decisions to be determined largely by the choices of employers and employees.”
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The discrimination against rural hospitals reflects the preferences of match participants.
- Rests on an assumption: The best teaching hospitals tend to be in urban areas, and urban areas tend to fill their positions far more effectively, and with better students, than rural hospitals.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Emergent bias poses a potential problem for any legal expert system, especially in a society where legal systems depend on evolving case law.”
§ Bias in Computer Systems > 3.3 The British Nationality Act Program (BNAP)
Tests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We thus infer that in this case the biased designs were unintended and, instead, reflected gender-biases deeply rooted in the culture at large.”
§ Bias in Computer Systems > 4. CONSIDERATIONS FOR MINIMIZING BIAS IN COMPUTER SYSTEM DESIGN
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“As Sabre and Apollo illustrate, biases in computer systems can be difficult to identify let alone remedy because of the way the technology engages and extenuates them.Computer systems, for instance, are comparatively inexpensive to disseminate, and thus, once developed, a biased system has the potential for widespread impact.If the system becomes a standard in the field, the bias becomes pervasive”
§ Bias in Computer Systems > INTRODUCTION
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Huff and Cooper report that along a number of dimensions the designs proposed by subjects in the gender-unspecified group closely resembled the designs proposed by subjects who designed for boys and were significantly different from the designs proposed by subjects who designed for girls.”
§ Bias in Computer Systems > 4. CONSIDERATIONS FOR MINIMIZING BIAS IN COMPUTER SYSTEM DESIGN
What the sources say
- Not checked — no full text of the sourcecites Huff and Cooper 1987 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“One source of this alleged bias lies in Sabre's and Apollo's algorithms for controlling search and display functions.In the algorithms, preference is given to”
§ Bias in Computer Systems > INTRODUCTION
Strength:hedged· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Thus, a shift in context of use may well create difficulties for a new set of users.”
§ Bias in Computer Systems > 2.2 Technical Bias
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Thus, the computer systems systematically downgrade and, hence, are biased against international carriers who fly few, if any, internal U.S. flights, and against internal carriers who do not fly international flights [Fotos 1988;Ott 1988].”
§ Bias in Computer Systems > INTRODUCTION
What the sources say
- Not matchedcites Fotos 1988
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites Ott 1988
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This bias typically emerges some time after a design is completed, as a result of changing societal knowledge, population, or cultural values.”
§ Bias in Computer Systems > 2.2 Technical Bias
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“One is that the interface design compounds the bias in the reservation systems.Lists of ranked flight options are displayed screen by screen.Each screen displays only two to five options.The advantage to a carrier of having its flights shown on the first screen is enormous since 90% of the tickets booked by travel agents are booked by the first screen display [Taib 1990].”
§ Bias in Computer Systems > INTRODUCTION
What the sources say
- Not matchedcites Taib 1990
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Or consider again the case of technical bias with the MLSA (which favors users with short jobs over long jobs).While technical bias is embedded in the program, the bias is a phenomenon of the system in use, in a context wherein users with short and long jobs outpace the system's capacity.”
§ Bias in Computer Systems > 4. CONSIDERATIONS FOR MINIMIZING BIAS IN COMPUTER SYSTEM DESIGN
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“In their study, subjects were asked to propose designs for software to teach seventh graders the correct use of commas.One group of subjects was asked to design the software for seventh-grade boys, the second group to design for seventh-grade girls, and the third group to design for seventh-graders, gender unspecified.”
§ Bias in Computer Systems > 4. CONSIDERATIONS FOR MINIMIZING BIAS IN COMPUTER SYSTEM DESIGN
What the sources say
- Not checked — no full text of the sourcecites Huff and Cooper 1987 source
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This type of bias can enter a system either through the explicit and conscious efforts of individuals or institutions, or implicitly and unconsciously, even in spite of the best of intentions.”
§ Bias in Computer Systems > 2.1 Preexisting Bias
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Sources of technical bias can be found in several aspects of the design process, including limitations of computer tools such as hardware, software, and peripherals; the process of ascribing social meaning to algorithms developed out of context; imperfections in pseudorandom number generation; and the attempt to make human constructs amenable to computers, when we quantify the qualitative, discret”
§ Bias in Computer Systems > 2.2 Technical Bias
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The constraint inherent in the NRMP algorithm, in which preference is given to hospital choices when conflicts in rankings occur, duplicates what happens in an actual admissions process without a computerized matching program”
§ Bias in Computer Systems > 3.1 The National Resident Match Program (NRMP)
What the sources say
- Not matchedcites Graettinger and Peranson 1981b
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim.
- Not matched
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Whatever ranking algorithm is used, if it systematically places certain airlines' flights on initial screens and other airlines' flights on later screens, the system will exhibit technical bias.”
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✗ Based: failsProbably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“They can also reflect the personal biases of individuals who have significant input into the design of the system, such as the client or system designer.”
§ Bias in Computer Systems > 2.1 Preexisting Bias
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“those responsible for maintaining the system responded conscientiously to this societal change and modified the system's algorithm to place couples more fairly [Roth 1990].”
§ Bias in Computer Systems > 4. CONSIDERATIONS FOR MINIMIZING BIAS IN COMPUTER SYSTEM DESIGN
What the sources say
- Not checked — no full text of the sourcecites Roth 1990 source
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Preexisting biases may originate in society at large, in subcultures, and in formal or informal, private or public organizations and institutions.”
§ Bias in Computer Systems > 2.1 Preexisting Bias
Strength:hedged· not yet calibratedCausal:conditional· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✗ Based: failsProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“Should the accumulation of case law lead to changes in the way the Act is interpreted-say, by granting new subgroups British citizenship-BNAP would systematically misinform members of this subgroup regarding their status as British citizens [Leith 1986].”
§ Bias in Computer Systems > 3.3 The British Nationality Act Program (BNAP)
What the sources say
- Not checked — no full text of the sourcecites Leith 1986 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“In total, we examined 17 computer systems from diverse fields including banking, commerce, computer science, education, medicine, and law.”
§ Bias in Computer Systems > 2. FRAMEWORK FOR ANALYZING BIAS IN COMPUTER SYSTEMS
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We derived our framework by examining actual computer systems for bias.Instances of bias were identified and characterized according to their source, and then the characterizations were generalized to more abstract categories.These categories were further refined by their application to other instances of bias in the same or additional computer systems.”
§ Bias in Computer Systems > 2. FRAMEWORK FOR ANALYZING BIAS IN COMPUTER SYSTEMS
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“although we have talked about bias in computer systems, the presence of bias is not so much a feature inherent in the system independent of the context of use, but an aspect of a system in use.”
§ Bias in Computer Systems > 4. CONSIDERATIONS FOR MINIMIZING BIAS IN COMPUTER SYSTEM DESIGN
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence.
The paper relies on this without support.
In cases of conflict, there is no good rationale for favoring hospital programs at the expense of medical students.
“We are inclined to answer yes because in cases of conflict there does not appear to be a good rationale for favoring hospital programs at the expense of students.”
The paper relies on this without support.
The discrimination against rural hospitals reflects the preferences of match participants.
“Namely, the discrimination reflects the preferences of match participants, and it is reasonable in our view for employment decisions to be determined largely by the choices of employers and employees.”
The paper relies on this without support.
The 17 computer systems examined are representative enough to generalize the framework to computer systems generally.
“In total, we examined 17 computer systems from diverse fields including banking, commerce, computer science, education, medicine, and law.”
The paper relies on this without support.
The illustrative examples in Table I portray plausible cases of bias.
“The illustrative examples portray plausible cases of bias.”
The paper relies on this without support.
The best teaching hospitals tend to be in urban areas, and urban areas tend to fill their positions far more effectively, and with better students, than rural hospitals.
“Because the best teaching hospitals tend to be in urban areas, the urban areas tend to fill their positions far more effectively, and with better students, than rural hospitals.”
The authors state this as an assumption.
The MLSA system is not saturated with too many users.
“assuming the system is not saturated with too many users”
The paper relies on this without support.
BNAP was designed in a research environment among people with sophisticated knowledge of immigration law.
“First, the system was designed in a research environment, among people with sophisticated knowledge of immigration law.”
The paper relies on this without support.
BNAP's users are likely to be at best paralegal or immigration counselors in Britain, if not lay persons in foreign countries with only limited access to British legal expertise.
“Its users, however, are likely to be at best paralegal or immigration counselors in Britain, if not lay persons in foreign countries with only limited access to British legal expertise.”
The paper relies on this without support.
Some of BNAP's queries require expert knowledge to answer.
“Some of the program's queries, for example, require expert knowledge to answer.”
The paper relies on this without support.
Nonexperts advising British citizen hopefuls are not alerted to alternative legal frameworks that complement the British Nationality Act.
“More generally, nonexperts advising British citizen hopefuls are not alerted to alternative legal frameworks that complement the British Nationality Act.”
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In the citing paper
“The multi-metric approach (Figure S1) makes explicit potential trade-offs and helps ensure the nonaccuracy desiderata are not treated as second-class citizens to accuracy (see Ref. 13).”
From Holistic Evaluation of Language Models (2023) · cites this paper as [13]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“research has repeatedly shown that these systems can in fact encode biases into decisions 124 .”
From Administrative law and the machines of government: judicial review of automated public-sector decision-making (2019) · cites this paper as B Friedman and H Nissenbaum 'Bias in Computer Systems' (1996)
The cited source says what the claim attributes to it.
In the citing paper
“The risk of”
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The cited source says what the claim attributes to it.
In the citing paper
“Bias or opacity are far from newly observed characteristics of computer systems generally [26, 11, 24], but these issues have been exacerbated by the rapidly expanding numbers of data-driven information systems entering decision-making processes.”
From Fairness and Accountability Design Needs for Algorithmic Support in High-Stakes Public Sector Decision-Making (2018) · cites this paper as [26]
In the citing paper
“These decisions may be based on factors of ethical importance (e.g., ethnic, gender, or religious grounds) and irrelevant to the decision-making at hand, or they may be relevant but legally protected as a nondiscriminatory characteristic (Friedman and Nissenbaum 1996).”
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In the citing paper
“On this account, the apparent problem to which data science is a solution determines whether it happens to serve morally defensible ends.”
From Problem Formulation and Fairness (2019) · cites this paper as [17]
In the citing paper
“Corresponding with [14] this outcome systematically disadvantages individuals of one gender by preferring the other at the topk positions.”
From FA*IR: A Fair Top-k Ranking Algorithm (2017) · cites this paper as [14]
In the citing paper
“While technical factors, such as biased data and design choices, play an important role, biases can also arise from the context of use, for example, how human users interpret system outputs or from a mismatch between the capabilities and values assumed in the design of the system and those of its actual users (Danks & London, 2017; Friedman & Nissenbaum, 1996).”
From Digital ageism: challenges and opportunities in artificial intelligence for older adults (2022) · cites this paper as Friedman & Nissenbaum, 1996
In the citing paper
“and to data protection, privacy, and other human rights issues 11”
From Administrative Law and the Machines of Government: Judicial Review of Automated Public-Sector Decision-Making (2018) · cites this paper as [11]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Table II gives conflicting years for its source
MinorThe table caption dates the Williams et al. source to 1991, while the paper's reference entry for that work dates it to 1981.
“Table II.The Simplest Case of Rank-Order Lists in which the Desires of Students and Programs are in Conflict (Reprinted from Williams et al. [1991], by permission of the New England Journal of Medicine)”
“18. WILLIAMS, K. J., WERTH, V. P., AND WOLFF, J. A. 1981. An analysis of the resident match.”
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Items 701–800 of 1,155
Ethics and AI StartupsPreprint
Bessen, J., Impink, S. M., Reichensperger, L., & Seamans, R. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.3895939 · Cited by 5
Moral Approaches to AI: Missing Power and Marginalized StakeholdersPreprint
Villegas-Galaviz, C., & Martin, K. E. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4099750 · Cited by 4
“We talk about bias only when unfair discrimination is systematically, and it is combined with an unfair outcome (Friedman and Nissenbaum, 1996).”
BackgroundNLPositionality: Characterizing Design Biases of Datasets and Models
Santy, S., Liang, J. T., Bras, R. L., Reinecke, K., & Sap, M. (2023) · arXiv · doi:10.48550/arxiv.2306.01943 · Cited by 31
“Based on Friedman and Nissenbaum (1996)’s framework on bias, social biases are pre-existing biases in society, whereas design biases are emergent biases that originate from the computing system itself.”
MethodImplementing and Evaluating Trustworthy Conversational Agents for Children
Escobar-Planas, M., Ruiz-Sánchez, R., Frau, P., Charisi, V., Martínez-Hinarejos, C.-D., Gómez, E., & Merino, L. (2025) · Communications in computer and information science · doi:10.1007/978-3-031-82633-7_29 · Cited by 3
Otuu, O. O., & Sahoo, D. R. (2025) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714168 · Cited by 3
“Phase 1: Identify stakeholders and form teams of participants: In the first phase, researchers should conceptually investigate [13] and identify stakeholders and form teams of participants to lay the groundwork for effectively achieving common goals.”
InfluentialCOBIAS: Assessing the Contextual Reliability of Bias Benchmarks for Language Models
Govil, P., Jain, H., Bonagiri, V. K., Chadha, A. R., Kumaraguru, P., Gaur, M., & Dey, S. (2025) · ACM Web Science Conference (WebSci) · doi:10.1145/3717867.3717923 · Cited by 11
“Bias in computer systems has been a research topic for over 35 years [18, 19, 38].”
Reframing Diversity in Computing on the Basis of Genders
Rode, J. A., Dugas, P. O. T., & Kerne, A. (2025) · Computer Supported Cooperative Work (CSCW) · doi:10.1007/s10606-025-09518-0 · Cited by 4
“Research shows questions in science tend to be framed, likely as a result of implicit biases 19 (Friedman and Nissenbaum 1996) by white, cisgendered, able-bodied men, who are in the majority.”
Gender inclusive language generation framework: A reasoning approach with RAG and CoT
Chinnan, S. P. M., Drury‐Grogan, M. L., & Chakravarthi, B. R. (2025) · Knowledge-Based Systems · doi:10.1016/j.knosys.2025.114092 · Cited by 4
The fall and rise of Iruda: Reassembling AI through ethics-in-action
Kwon, Y., & Hong, S. (2025) · Social Studies of Science · doi:10.1177/03063127251360397 · Cited by 4
Understanding Perceptions of Algorithmic Bias Through the Risk Perception and Attitude Framework
Overbye-Thompson, H. E., Garcia, E. A., Zhang, X., & Wang, L. H. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2546661 · Cited by 3
“…designed and implemented, leading to unintended disparities in how different users are treated (Overbye-Thompson et al., 2024), while moral bias refers to when algorithms produce discriminatory outcomes for specific groups or individuals, whether deliberately or not (Friedman & Nissenbaum, 1996).”
Between Connection and Control: Technology Appropriation by Older Adults in Iran
Ghadamighalandari, P., Amirkhani, S., Aal, K., Müller, C., & Wulf, V. (2025) · International Conference on Communities and Technologies (C&T) · doi:10.1145/3742800.3742833 · Cited by 6
“Friedman [18] argues that computer technologies should be designed based on human values first.”
Algorithmic Status Inequality: An Integrative Perspective on AI‐Driven Social Stratification
Wu, J. (2026) · Journal of Management Studies · doi:10.1111/joms.70134 · Cited by 4
Álvarez, J. L. D. (2021) · IUS ET SCIENTIA · doi:10.12795/ietscientia.2021.i01.16 · Cited by 6
Stricker, J., & Verständig, D. (2023) · MedienPädagogik: Zeitschrift für Theorie und Praxis der Medienbildung · doi:10.21240/mpaed/jb20/2023.09.04.x · Cited by 1
A Unified Meta-Learning Framework for Fair Ranking With Curriculum Learning
Wang, Y., Tao, Z., & Fang, Y. (2024) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2024.3377644 · Cited by 3
“Specifically,weoptimizeametalearnerfromasampled dataset( meta-dataset ), and meanwhile train a ranking model on the whole ( biased ) dataset.”
BackgroundEmbury, J., Nara, A., Rey, S. J., et al. (2024) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2024.2358399 · Cited by 3
“Synthetic population biases must be addressed because they ‘systematically and unfairly discriminate against certain individuals or groups of individuals in favor of others’ (Friedman and Nissenbaum, 1996, p. 332).”
Ghose, A., Pallav, P., & Ali, S. M. (2025) · Advances in finance, accounting, and economics book series · doi:10.4018/979-8-3693-7036-0.ch007 · Cited by 4
FanFAIR: sensitive data sets semi-automatic fairness assessment
Gallese, C., Scantamburlo, T., Manzoni, L., Giannerini, S., & Nobile, M. S. (2025) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-025-03184-4 · Cited by 3
Ethical, Legal, and Social Issues (ELSI) in Mental Health Informatics
Subbian, V., Galvin, H. K., Petersen, C. C., & Solomonides, A. E. (2021) · Health informatics · doi:10.1007/978-3-030-70558-9_18 · Cited by 3
Biases within Digital Repositories: The Getty Research Portal
Sever, H. (2020) · Stedelijk Studies Journal · doi:10.54533/stedstud.vol010.art03 · Cited by 3
Citizen Participation and ICT for Urban Development in Oslo
Giannoumis, G. A., & Joneja, N. (2022) · Springer eBooks · doi:10.1007/978-3-030-99940-7_5 · Cited by 4
Centring dignity in algorithm development: testing a Dignity Lens
Ruster, L. P., Oliva‐Altamirano, P., & Daniell, K. A. (2022) · Australian Conference on Human-Computer Interaction (OzCHI) · doi:10.1145/3572921.3572938 · Cited by 4
“The Dignity Lens revealed to the team what [13] refer to as ‘individual preexisting bias’, and how this was entering the system implicitly and uncon-sciously.”
BackgroundFairSwiRL: fair semi-supervised classification with representation learning
Yang, S., Cerrato, M., Ienco, D., Pensa, R. G., & Esposito, R. (2023) · Machine Learning · doi:10.1007/s10994-023-06342-9 · Cited by 3
Artificial Intelligence in the Public Sector in Norway:
Corneliussen, H. G., Seddighi, G., Iqbal, A., et al. (2024) · Communications in computer and information science · doi:10.1007/978-3-031-53770-7_11 · Cited by 3
Unveiling Gender Biases in Recruitment: A Natural Language Processing Approach
Barriuso, M. I. (2024) · Journal of Global Economics Management and Business Research · doi:10.56557/jgembr/2024/v16i18634 · Cited by 4
El-Sayed, S., & Paspalj, F. (2024) · Research Ethics · doi:10.1177/17470161241247686 · Cited by 3
“These principles have gained prominence in recent years as essential components of ethical data science and AI practices (AI HILEG, 2019; Friedman and Nissenbaum, 1996).”
Che, C. V. (2024) · OALib · doi:10.4236/oalib.1111698 · Cited by 3
Value‐centred interaction design methods
Knight, J. (2008) · Journal of Information Communication and Ethics in Society · doi:10.1108/14779960810921132 · Cited by 3
“Others (Friedman and Nissenbaum, 1996; Fogg, 2001; Thimbleby, 2001) have also raised the need for social responsibility in designing interactive technology albeit with a focus on impact rather than opportunity.”
BackgroundLawrence, E., & Fry, R. J. (2016) · The Library Quarterly · doi:10.1086/688030 · Cited by 3
“…studies, science and technology studies, etc., have written extensively on the various ways in which digital technologies (necessarily) function as value-laden artifacts of power (see, for example, Pacey 1983; Sclove 1995; Friedman and Nissenbaum 1996; Fleischmann 2007; Brock 2011; Noble 2013).”
BackgroundMolekulares maschinelles Lernen: Die Zukunft der Synthesechemie?
Pflüger, P. M., & Glorius, F. (2020) · Angewandte Chemie · doi:10.1002/ange.202008366 · Cited by 3
Software Engineer Islamic Ethics: An interactive web-based model
Hameed, S. A., Al-Khateeb, K. A. S., & Mutaz, Z. (2010) · International Conference on Computer and Communication Engineering · doi:10.1109/iccce.2010.5556785 · Cited by 3
Ethical Challenges of Ubiquitous Computing
Wiegerling, P. D. K., Capurro, R., Britz, J., Hausmanninger, T., Nakada, M., & Apel, M. (2007) · Cited by 3
Zimmer, M. T. (2005) · Cited by 3
Towards a unified conceptual model for surveillance theories
Barn, B. S., & Barn, R. (2018) · IEEE/ACM International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS) · doi:10.1145/3183428.3183429 · Cited by 3
“humans but this of course returns us to our opening introduction of how values are embedded in the design of software [17].”
BackgroundRiedl, M. J. (2022) · Journalism Studies · doi:10.1080/1461670x.2021.2024084 · Cited by 3
“Friedman and Nissenbaum (1996) differentiate between three different kinds of biases in computer systems: Pre-existing, technical, and emergent, wherein the pre-existing notion ties in with cultural and societal factors that shape the technical system, the technical bias refers to constraints…”
BackgroundOn the Lack of Legal Regulation in Conceptual Modeling
von Lewinski, K., & Scherzinger, S. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-22036-4_9 · Cited by 3
Responsible Conduct of Research with Computational Models and Simulations
Kijowski, D. J. (2011) · Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) · Cited by 3
Nurturing Software: How Societal Institutions Shape the Development of Software
Shah, R., & Kesan, J. P. (2004) · Cited by 3
Toward a value‐analytic approach to information standards
Dobreski, B. (2018) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.2018.14505501013 · Cited by 3
“In information science, value analysis has been applied to artifacts such as algorithms (Friedman & Nissenbaum, 1996) and tweets (Fleischmann et al., 2012), though at present, it has not been applied to information standards.”
MethodA multilingual automated web usability evaluation agent
Abulkhair, M. (2004) · White Rose eTheses Online (University of Leeds, The University of Sheffield, University of York) · Cited by 3
Organizing Markets: The Structuring of Neoliberalism in the U.S. Airline Industry
Avent‐Holt, D. (2019) · ScholarWorks@UMassAmherst (University of Massachusetts Amherst) · doi:10.7275/8z4d-d912 · Cited by 3
Science and Technology, Social Study of: Computers and Information Technology
Bowker, G. C., & Star, S. L. (2015) · Elsevier eBooks · doi:10.1016/b978-0-08-097086-8.85024-2 · Cited by 3
The People’s Republic of Youtube? Interrogating Rhetorics of Internet DemocracyPreprint
Marwick, A. E. (2007) · SSRN Electronic Journal · Cited by 3
Privacy by design: An assessment of law enforcement drones
Anderson, S. (2014) · DigitalGeorgetown (Georgetown University Library) · Cited by 3
Designing for Participation and Change in Digital InstitutionsPreprint
Krafft, P. M., Keegan, B., & Frey, S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.08728 · Cited by 4
“There is a relatively long tradition in the areas of human-computer interaction and computer-supported cooperative work interrogating how values are embedded in software and technological artifacts [81, 24, 23].”
BackgroundInclusion, equality and bias in designing online mass deliberative platformsPreprint
Shortall, R., Itten, A. V., van der Meer, M., Murukannaiah, P. K., & Jonker, C. M. (2021) · arXiv (Cornell University) · Cited by 3
In Oxford Handbook on AI Governance: The Role of Workers in AI Ethics and GovernancePreprint
Luka, N., & Tan, J. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2108.07700 · Cited by 3
When Platforms Act Opportunistically: The Ethics of Platform GovernancePreprint
Martin, K. E., Guo, H. Y., & Easley, R. F. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4202821 · Cited by 3
User-Based Algorithmic AuditingPreprint
Hacohen, U. Y. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4540163 · Cited by 3
Report of the 1st Workshop on Generative AI and LawPreprint
Cooper, A. F., Lee, K., Grimmelmann, J., Ippolito, D., Callison-Burch, C., Choquette-Choo, C. A., Mireshghallah, N., Brundage, M., Mimno, D., Choksi, M. Z., et al. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4634513 · Cited by 32
Differential Replication for Credit Scoring in Regulated Environments
Unceta, I., Nin, J., & Pujol, O. (2021) · Entropy · doi:10.3390/e23040407 · Cited by 2
CIDER: A Method to Teach Practical Critical Software Design Skills
Oleson, A. (2022) · ACM Conference on International Computing Education Research (ICER) · doi:10.1145/3501709.3544295 · Cited by 2
“My research targets five student learning challenges in particular: motivating critical UI design [2]; connecting UI design features to assumptions [5]; designing for diversity [3]; moving from abstract understandings to concrete critical UI design actions [1]; and avoiding stereotyping [12].”
BackgroundJusticia algorítmica: un enfoque sociotécnico
Bolado, A. B. (2023) · Estudios Penales y Criminológicos · doi:10.15304/epc.44.8838 · Cited by 7
The Need for Emotional Intelligence in Human-Computer Interactions
Goswami, S. A., Dave, S., & Patel, K. C. K. (2024) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-2794-4.ch006 · Cited by 2
Temporal Extraction and Retrieval
Alonso, O., & Spaniol, M. (2024) · ACM eBooks · doi:10.1145/3674127.3674137 · Cited by 2
Tonellotto, N. (2024) · ACM eBooks · doi:10.1145/3674127.3674130 · Cited by 3
Ethical considerations in AI-powered language technologies: insights from East and West Armenian
Ishkhanyan, A. (2025) · AI and Ethics · doi:10.1007/s43681-025-00716-6 · Cited by 2
Ending well: Values in concluding or transitioning community educational technology projects
Pitt, C. R. (2025) · British Journal of Educational Technology · doi:10.1111/bjet.13598 · Cited by 2
Prompting Fairness: How End Users Can Mitigate Bias in AI Systems
Marsden, N. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-93415-5_4 · Cited by 2
Sayer, H., Polajnar, T., & Spence, R. (2025) · The Police Journal Theory Practice and Principles · doi:10.1177/0032258x251372357 · Cited by 3
“This is where algorithms systematically and unfairly discriminate against certain individuals or groups of individuals in favour of others (Friedman and Nissenbaum, 1996), as shown when the previously discussed COMPAS algorithm disproportionally fl agged African Americans.”
Still More Shades of Null: An Evaluation Suite for Responsible Missing Value Imputation
Khan, F. A., Herasymuk, D., Protsiv, N., & Stoyanovich, J. (2025) · Proceedings of the VLDB Endowment · doi:10.14778/3746405.3746416 · Cited by 8
“This situation is consistent with MAR missingness, and it points to pre-existing bias — a situation where data reflects a history of societal discrimination [23].”
Lloyd, T., Nguyen, T., Levy, K. E. C., & Naaman, M. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791889 · Cited by 7
“TikTok, Meta, Twitter/X, YouTube How public is the data needed to evaluate the impact of notes on engagement?”
Beyond Neutrality: Mapping Two Decades of Research on Machine Translation Bias (2005–2024)
Li, Y., & Song, X. (2025) · SAGE Open · doi:10.1177/21582440251392700 · Cited by 2
“From the perspective of the bias sources, Friedman and Nissenbaum (1996) proposed a triadic model of bias based on 17 different computer systems in fields such as banking, business, and education.”
A theoretical model of AI bias mitigation: incentives, regulation and equilibrium
Bera, S., & Bera, I. (2025) · Journal of Information Communication and Ethics in Society · doi:10.1108/jices-06-2025-0138 · Cited by 2
Making problems: interdisciplinary collaboration and AI ethics
Moats, D., Holtrop, T., van Eck, N. J., Varga, J., Waltman, L., & Dechesne, F. (2025) · Science as Culture · doi:10.1080/09505431.2025.2584759 · Cited by 3
Human Rights in the Shadow of AI: Confronting Bias and Accountability
Ghayoumi, M., & Ghazinour, K. (2025) · IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON) · doi:10.1109/uemcon67449.2025.11267585 · Cited by 2
“Rooted in historical inequities, these biases can unintentionally discriminate against vulnerable groups, undermining rights to equality, fairness, and dignity [2][3][16].”
InfluentialLaw, J. (2025) · AI and Ethics · doi:10.1007/s43681-025-00927-x · Cited by 2
“Winner (1980) argues that technologies can have political properties, while Friedman and Nissenbaum (1996) document systematic forms of bias embedded in computer systems.”
Robotic Bias and Its Dimensions
Furlanis, T., Brščić, D., & Kanda, T. (2026) · ACM/IEEE International Conference on Human-Robot Interaction (HRI) · doi:10.1145/3757279.3785613 · Cited by 2
“Following Friedman and Nissenbaum [35], we understand bias in technological systems as “systematic and unfair discrimination against certain individuals or groups in favor of others.””
InfluentialRestricted versus general complexity: epistemological foundations for reflexive systems practice
Ascencio, R. R. L. (2026) · Kybernetes · doi:10.1108/k-02-2026-0394 · Cited by 3
Critical design literacy through reflection in design
Maus, I. G. (2021) · doi:10.21606/drs_lxd2021.03.228 · Cited by 2
In-group and Out-group Performance Bias in Facial Retouching Detection
Bharati, A., Connors, E., Mayank Vatsa, A., Singh, R., & Bowyer, K. W. (2022) · IEEE International Joint Conference on Biometrics (IJCB) · doi:10.1109/ijcb54206.2022.10007942 · Cited by 3
“In the context of computing, Fried-man and Nissenbaum define bias as systematically and un-fairly discriminating against certain individuals or groups of individuals in favor of others [24].”
MethodHammer or Measuring Tape? Artificial Intelligence and Justice in Healthcare
Heinrichs, J.-H. (2023) · Cambridge Quarterly of Healthcare Ethics · doi:10.1017/s0963180123000257 · Cited by 2
Egbert, S. (2024) · Springer eBooks · doi:10.1007/978-3-658-42565-4_14 · Cited by 2
Perceptions in Pixels: Analyzing Perceived Gender and Skin Tone in Real-world Image Search Results
Gleason, J. M., Ghosh, A., Robertson, R. E., & Wilson, C. (2024) · International World Wide Web Conference (WWW) · doi:10.1145/3589334.3645666 · Cited by 2
“According to Friedman and Nis-senbaum [8] if it “systematically and unfairly discriminates against certain individuals or groups.””
Touameur, O., & Harrag, F. (2023) · doi:10.1109/eiceeai60672.2023.10590431 · Cited by 2
“…discriminate against certain individuals or groups of individuals in favor of others [by denying] an opportunity for a good or [assigning] an undesirable outcome to an individual or groups of individuals on grounds that are unreasonable or ”inappropriate” (Friedman and Nissenbaum, 1996) [10].”
BackgroundIdentifying Characteristics of Reflection Triggers in Data Science Ethics Education
Linke, D., & Müller-Birn, C. (2024) · Mensch und Computer (MuC) · doi:10.1145/3670653.3677486 · Cited by 2
A Framework for Defining Algorithmic Fairness in the Context of Information Access
Udoh, E. S., Yuan, X., & Rorissa, A. (2024) · Proceedings of the Association for Information Science and Technology · doi:10.1002/pra2.1077 · Cited by 4
“In its various manifestations including the context of information access, bias can be grouped into exogenous and endogenous (Joachims (2021) and into three major categories: preexisting, technical, and emergent (Friedman & Nissenbaum, 1996).”
Artfully Integrating AI: Proceeding Responsibly With Worker-Centered Best Practices
Fox, S., & Shorey, S. (2024) · Springer eBooks · doi:10.1007/978-3-031-66528-8_4 · Cited by 3
Dar, A. A., Yadav, S. S., Tripathi, R. K., Albalawi, O., Jain, A., & Gautam, P. L. (2024) · Advances in educational technologies and instructional design book series · doi:10.4018/979-8-3693-6170-2.ch011 · Cited by 3
Verberne, S. (2024) · ACM eBooks · doi:10.1145/3674127.3674141 · Cited by 5
Ferro, N., & Maistro, M. (2024) · ACM eBooks · doi:10.1145/3674127.3674132 · Cited by 3
Privacy in Information Retrieval
Soboroff, I. M. (2024) · ACM eBooks · doi:10.1145/3674127.3674139 · Cited by 2
Sensors, Techniques, and Future Trends of Human-Engagement-Enabled Applications: A Review
Dai, Z., Zakka, V. G., Manso, L. J., Rudorfer, M., Bernardet, U., Zumer, J. M., & Kavakli, M. (2024) · Algorithms · doi:10.3390/a17120560 · Cited by 2
Martínez, A. R. (2024) · European yearbook of constitutional law · doi:10.1007/978-94-6265-647-5_7 · Cited by 2
Is software design gender biased? A study on software-design effect on task performance
Elnagar, S. (2024) · International Journal of Information Management Data Insights · doi:10.1016/j.jjimei.2024.100312 · Cited by 4
Palma, Ş. P., & Alvarez-Vidal, S. (2024) · transLogos Translation Studies Journal · doi:10.29228/translogos.67 · Cited by 1
Navigating the complex terrain: An in-depth analysis of the challenges of the metaverse
Sachdeva, P., & Mitra, A. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-24132-1.00002-8 · Cited by 2
Understanding and Mitigating Gender Bias in Information Retrieval Systems
Seyedsalehi, S., Bigdeli, A., Arabzadeh, N., AlMousawi, B., Marshall, Z., Zihayat, M., & Bagheri, E. (2025) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000103 · Cited by 3
Navigating AI and Children's Rights in Corporate Practices
Bohlens, C. (2025) · Advances in human and social aspects of technology book series · doi:10.4018/979-8-3693-9035-1.ch011 · Cited by 3
Ron, G., Leder, S., Siriwardena, L., Kropp, C., Menges, A., & Wortmann, T. (2025) · Construction Robotics · doi:10.1007/s41693-025-00164-y · Cited by 3
“In human-computer and human–robot interaction (HCI, HRI), reviewing embedded biases (Friedman and Nissenbaum 1996; Schelenz 2023; Wagman and Parks 2021), and diverse user needs (Suchman 2007; Bardzell 2010; Schelenz 2023).”
Gender-based cognitive bias and design thinking in the work of Finnish IT professionals
Kronqvist, A., & Rousi, R. A. (2025) · Information and Software Technology · doi:10.1016/j.infsof.2025.107910 · Cited by 2
17 Years of Fintech for Financial Inclusion: A Systematic Review and Critical Value Analysis
Verma, P., Becker, C., & Sabie, S. (2025) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3757539 · Cited by 2
“The HCI and CSCW communities have consistently drawn attention to the biases and values in the design of information and computing systems (e.g., [32, 35, 39, 46, 53, 54, 56, 163, 180]).”
Cognitive Bias in AI Recommendations: Understanding and Mitigating Human-AI Decision-Making Errors
Aich, P. (2025) · International Conference on Human-Agent Interaction (HAI) · doi:10.1145/3765766.3765887 · Cited by 1
Rahman, A. T. M. M., Ahmed, S. I., & Sultana, S. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790962 · Cited by 2
Lee, D., Ju, J., Song, H., & Park, H. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791249 · Cited by 2
“Friedman and Nissenbaum [41] argue that systematic differences only constitute bias when they produce unfair outcomes.”
When users control the algorithms: Values expressed in practices on the twitter platform
Burrell, J., Kahn, Z., Jonas, A., & Griffin, D. (2019) · eScholarship (California Digital Library) · doi:10.1145/33592407 · Cited by 2
Machinic enculturation, copyright bots, and the aesthetics of composing mashups for machines
Coleman, M. C., & Anthoney, M. (2020) · Journal of AESTHETICS & CULTURE · doi:10.1080/20004214.2020.1831841 · Cited by 2
Diversity-sensitive social platforms and responsibility
Reinhardt, K. (2021) · Információs Társadalom · doi:10.22503/inftars.xxi.2021.2.4 · Cited by 2
Künstliche Intelligenz, Bias und Versicherungen – Eine technische und rechtliche Analyse
Pohlmann, P., Vossen, G., Everding, J., & Scheiper, J. (2022) · Zeitschrift für die gesamte Versicherungswissenschaft · doi:10.1007/s12297-022-00528-1 · Cited by 3
Communication Technology and Exchanging Financial Assets: A Historical Perspective
Booth, E. B., Booth, G. G., & Broussard, J. P. (2014) · Business and Economic Research · doi:10.5296/ber.v4i2.6643 · Cited by 2
“In thinking about these and related questions, however, we must also consider, as Friedman & Nissenbaum (1996) point out, that computer software does contain human biases.”
Background
Metadata
- Authors
- Friedman, B., & Nissenbaum, H.
- Affiliations
- Colby College (US)
- Princeton University (US)
- Venue
- ACM Transactions on Information Systems
- Published
- 1996-07
- Volume
- 14
- Issue
- 3
- Pages
- 330-347
- ISSN
- 1046-8188 (ISSN-L)
- 1558-2868
- OpenAlex
- W2006447892
- Cited by
- 1,203
- References
- 13
- Citations by year
- 2026: 102 · 2025: 149 · 2024: 151 · 2023: 121 · 2022: 126 · 2021: 133 · 2020: 79 · 2019: 70 · 2018: 50 · 2017: 21 · 2016: 29 · 2015: 18 · 2014: 18 · 2013: 16 · 2012: 8
- FWCI
- 17.25
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- ACM Transactions on Information Systems (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Law › Artificial Intelligence in Law
- Keywords
- technical bias, social institutions, technological constraints, societal impact of technology
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