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The system described in the paper looks for [[:w:WP:Red link|red links]] in Wikipedia and classifies them based on their context. To find section titles, it then looks for similar existing articles. With these titles, the system searches the web for information, and eventually uses content summarization and a paraphrasing algorithm. The researchers uploaded 50 of these automatically created articles to Wikipedia, and found that 47 of them survived. Some were heavily edited after upload, others not so much.
The system described in the paper looks for [[:w:WP:Red link|red links]] in Wikipedia and classifies them based on their context. To find section titles, it then looks for similar existing articles. With these titles, the system searches the web for information, and eventually uses content summarization and a paraphrasing algorithm. The researchers uploaded 50 of these automatically created articles to Wikipedia, and found that 47 of them survived. Some were heavily edited after upload, others not so much.
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While I was enthusiastic about the results, I was surprised by the suboptimal quality of the articles I reviewed – three that were mentioned in the paper. After a brief discussion with the authors, a wider discussion was initiated [[mailarchive:wiki-research-l/2016-August/005324.html|on the Wiki-research mailing list]]. This was followed by an entry on the [[:w:Wikipedia:Administrators' noticeboard/IncidentArchive931#Moving discussion from wikimedia research mailing list|English Wikipedia administrators' noticeboard]] (which includes a list of all accounts used for this particular research paper). The discussion led to the removal of most of the remaining articles.
While I was enthusiastic about the results, I was surprised by the suboptimal quality of the articles I reviewed – three that were mentioned in the paper. After a brief discussion with the authors, a wider discussion was initiated [[mailarchive:wiki-research-l/2016-August/005324.html|on the Wiki-research mailing list]]. This was followed by an entry on the [[:w:Wikipedia:Administrators' noticeboard/IncidentArchive931#Moving discussion from wikimedia research mailing list|English Wikipedia administrators' noticeboard]] (which includes a list of all accounts used for this particular research paper). The discussion led to the removal of most of the remaining articles.
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A paper<ref>{{Cite journal| doi = 10.1007/s10676-016-9399-8| issn = 1388-1957| pages = 1–18| last = Laat| first = Paul B.| title = Profiling vandalism in Wikipedia: A Schauerian approach to justification| journal = Ethics and Information Technology| date = 30 April 2016| url = http://link.springer.com/article/10.1007/s10676-016-9399-8}}</ref> in the journal ''Ethics and Information Technology'' examines the "system of surveillance" that the English Wikipedia has built up over the years to deal with vandalism edits. The author, Paul B. de Laat from the University of Groningen, presents an interesting application of a theoretical framework by US law scholar [[:w:Frederick Schauer|Frederick Schauer]] that focuses on the concepts of rule enforcement and profiling. While providing justification for the system's efficacy and largely absolving it of some of the objections that are commonly associated with the use of profiling in e.g. law enforcement, de Laat ultimately argues that in its current form, it violates an alleged "social contract" on Wikipedia by not treating anonymous and logged-in edits equally. Although generally well-informed about both the practice and the academic research of vandalism fighting, the paper unfortunately fails to connect to an existing debate about very much the same topic – potential biases of artificial intelligence-based anti-vandalism tools against anonymous edits – that was begun last year<ref>See e.g. {{Cite web| last = Halfaker| first = Aaron| title = Disparate impact of damage-detection on anonymous Wikipedia editors| url = http://socio-technologist.blogspot.tw/2015/12/disparate-impact-of-damage-detection-on.html| date = December 6, 2015| publisher = Socio-technologist }}</ref> by the researchers developing ORES (an edit review tool that was just made available to all English Wikipedia users, see this week's [[:w:Wikipedia:Wikipedia Signpost/2016-09-06/Technology report|Technology report]]) and most recently discussed in the [[mw:Wikimedia_Research/Showcase#August_2016|August 2016 WMF research showcase]].
A paper<ref>{{Cite journal| doi = 10.1007/s10676-016-9399-8| issn = 1388-1957| pages = 1–18| last = Laat| first = Paul B.| title = Profiling vandalism in Wikipedia: A Schauerian approach to justification| journal = Ethics and Information Technology| date = 30 April 2016| url = http://link.springer.com/article/10.1007/s10676-016-9399-8}}</ref> in the journal ''Ethics and Information Technology'' examines the "system of surveillance" that the English Wikipedia has built up over the years to deal with vandalism edits. The author, Paul B. de Laat from the University of Groningen, presents an interesting application of a theoretical framework by US law scholar [[:w:Frederick Schauer|Frederick Schauer]] that focuses on the concepts of rule enforcement and profiling. While providing justification for the system's efficacy and largely absolving it of some of the objections that are commonly associated with the use of profiling in e.g. law enforcement, de Laat ultimately argues that in its current form, it violates an alleged "social contract" on Wikipedia by not treating anonymous and logged-in edits equally. Although generally well-informed about both the practice and the academic research of vandalism fighting, the paper unfortunately fails to connect to an existing debate about very much the same topic – potential biases of artificial intelligence-based anti-vandalism tools against anonymous edits – that was begun last year<ref>See e.g. {{Cite web| last = Halfaker| first = Aaron| title = Disparate impact of damage-detection on anonymous Wikipedia editors| url = http://socio-technologist.blogspot.tw/2015/12/disparate-impact-of-damage-detection-on.html| date = December 6, 2015| publisher = Socio-technologist }}</ref> by the researchers developing ORES (an edit review tool that was just made available to all English Wikipedia users, see this week's [[:w:Wikipedia:Wikipedia Signpost/2016-09-06/Technology report|Technology report]]) and most recently discussed in the [[mw:Wikimedia_Research/Showcase#August_2016|August 2016 WMF research showcase]].
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The paper first gives an overview of the various [[:w:Wikipedia:Cleaning up vandalism/Tools|anti-vandalism tools]] and bots in use, recapping an earlier paper<ref>{{Cite journal| doi = 10.1007/s10676-015-9366-9| issn = 1388-1957| volume = 17| issue = 3| pages = 175–188| last = Laat| first = Paul B. de| title = The use of software tools and autonomous bots against vandalism: eroding Wikipedia’s moral order?| journal = Ethics and Information Technology| date = 2 September 2015| url = http://link.springer.com/article/10.1007/s10676-015-9366-9}}</ref> where de Laat had already asked whether these are "eroding Wikipedia’s moral order" (following an even earlier [[m:Research:Newsletter/2014/May#cite_ref-14|2014 paper]] in which he had argued that new-edit patrolling "raises a number of moral questions that need to be answered urgently"). There, de Laat's concerns included the fact that some stronger tools ([[:w:Wikipedia:Rollback|rollback]], [[:w:Wikipedia:Huggle|Huggle]], and [[:w:Wikipedia:STiki|STiki]]) are available only to trusted users and "cause a loss of the required moral skills in relation to newcomers", and that they a lack of transparency about how the tools operate (in particular when more sophisticated artificial intelligence/machine learning algorithms such as neural networks are used). The present paper expands on a separate but related concern, about the use of "profiling" to pre-select which recent edits will be subject to closer human review. The author emphasizes that on Wikipedia this usually does not mean person-based [[:w:offender profiling|offender profiling]] (building profiles of individuals committing vandalism), citing only one exception in form of a 2015 academic paper – cf. our review: "[[m:Research:Newsletter/2015/August#Early_warning_system_identifies_likely_vandals_based_on_their_editing_behavior|Early warning system identifies likely vandals based on their editing behavior]]". Rather, "the anti-vandalism tools exemplify the broader type of profiling" that focuses on actions. Based on Schauer's work, the author asks the following questions:
The paper first gives an overview of the various [[:w:Wikipedia:Cleaning up vandalism/Tools|anti-vandalism tools]] and bots in use, recapping an earlier paper<ref>{{Cite journal| doi = 10.1007/s10676-015-9366-9| issn = 1388-1957| volume = 17| issue = 3| pages = 175–188| last = Laat| first = Paul B. de| title = The use of software tools and autonomous bots against vandalism: eroding Wikipedia’s moral order?| journal = Ethics and Information Technology| date = 2 September 2015| url = http://link.springer.com/article/10.1007/s10676-015-9366-9}}</ref> where de Laat had already asked whether these are "eroding Wikipedia’s moral order" (following an even earlier [[m:Research:Newsletter/2014/May#cite_ref-14|2014 paper]] in which he had argued that new-edit patrolling "raises a number of moral questions that need to be answered urgently"). There, de Laat's concerns included the fact that some stronger tools ([[:w:Wikipedia:Rollback|rollback]], [[:w:Wikipedia:Huggle|Huggle]], and [[:w:Wikipedia:STiki|STiki]]) are available only to trusted users and "cause a loss of the required moral skills in relation to newcomers", and that they a lack of transparency about how the tools operate (in particular when more sophisticated artificial intelligence/machine learning algorithms such as neural networks are used). The present paper expands on a separate but related concern, about the use of "profiling" to pre-select which recent edits will be subject to closer human review. The author emphasizes that on Wikipedia this usually does not mean person-based [[:w:offender profiling|offender profiling]] (building profiles of individuals committing vandalism), citing only one exception in form of a 2015 academic paper – cf. our review: "[[m:Research:Newsletter/2015/August#Early_warning_system_identifies_likely_vandals_based_on_their_editing_behavior|Early warning system identifies likely vandals based on their editing behavior]]". Rather, "the anti-vandalism tools exemplify the broader type of profiling" that focuses on actions. Based on Schauer's work, the author asks the following questions:
# "Is this profiling profitable, does it bring the rewards that are usually associated with it?"
# "Is this profiling profitable, does it bring the rewards that are usually associated with it?"
# "is this profiling approach towards edit selection justified? In particular, do any of the dimensions in use raise moral objections? If so, can these objections be met in a satisfactory fashion, or do such controversial dimensions have to be adapted or eliminated?"
# "is this profiling approach towards edit selection justified? In particular, do any of the dimensions in use raise moral objections? If so, can these objections be met in a satisfactory fashion, or do such controversial dimensions have to be adapted or eliminated?"
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[[File:DIN 4844-2 D-P014.svg|280px|right|But snakes are much more dangerous! According to Schauer, while general rules are always less fair than case-by-case decisions, their existence can be justified by other arguments.]]
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To answer the first question, the author turns to Schauer's work on rules, in a [https://link.springer.com/article/10.1007/s10676-016-9399-8#Sec5 brief summary] that is worth reading for anyone interested in Wikipedia policies and guidelines – although de Laat instead applies the concept to the "procedural rules" implicit in vandalism profiling (such as that anonymous edits are more likely to be worth scrutinizing).
To answer the first question, the author turns to Schauer's work on rules, in a [https://link.springer.com/article/10.1007/s10676-016-9399-8#Sec5 brief summary] that is worth reading for anyone interested in Wikipedia policies and guidelines – although de Laat instead applies the concept to the "procedural rules" implicit in vandalism profiling (such as that anonymous edits are more likely to be worth scrutinizing).
First, Schauer "resolutely pushes aside the argument from fairness: decision-making based on rules can only be less just than deciding each case on a particularistic basis ". (For example, a restaurant's "No Dogs Allowed" rule will unfairly exclude some well-behaved dogs, while not prohibiting much more dangerous animals such as snakes.) Instead, the existence of rules have to be justified by other arguments, of which Schauer presents four:
First, Schauer "resolutely pushes aside the argument from fairness: decision-making based on rules can only be less just than deciding each case on a particularistic basis ". (For example, a restaurant's "No Dogs Allowed" rule will unfairly exclude some well-behaved dogs, while not prohibiting much more dangerous animals such as snakes.) Instead, the existence of rules have to be justified by other arguments, of which Schauer presents four:
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De Laat also interprets "the Schauerian argument of ''reliability/predictability'' for those affected by the rule" in favor of vandalism profiling. Here, though, he fails to explain the benefits of vandals being able to predict which kind of edits will be subject to scrutiny. This also calls into question his subsequent remark that "it is unfortunate that the anti-vandalism system in use remains opaque to ordinary users". The remaining two of Schauer's four arguments are judged as less pertinent. But overall the paper concludes that it is possibile to justify the existence of vandalism profiling rules as beneficial via Schauer's theoretical framework.
De Laat also interprets "the Schauerian argument of ''reliability/predictability'' for those affected by the rule" in favor of vandalism profiling. Here, though, he fails to explain the benefits of vandals being able to predict which kind of edits will be subject to scrutiny. This also calls into question his subsequent remark that "it is unfortunate that the anti-vandalism system in use remains opaque to ordinary users". The remaining two of Schauer's four arguments are judged as less pertinent. But overall the paper concludes that it is possibile to justify the existence of vandalism profiling rules as beneficial via Schauer's theoretical framework.
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Police traffic stops: A good analogy for anti-vandalism patrol on Wikipedia?]]
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Police traffic stops: A good analogy for anti-vandalism patrol on Wikipedia?]]
Next, de Laat turns to question 2, on whether vandalism profiling is also morally justified. Here he relies on later work by Schauer, from a 2003 book, "Profiles, Probabilities, and Stereotypes", that studies such matters as profiling by tax officials (selecting which taxpayers have to undergo an audit), airport security (selecting passengers for screening) and by police officers (e.g. selecting cars for traffic stops). While profiling of some kind is a necessity for all these officials, the particular characteristics (dimensions) used for profiling can be highly problematic (see e.g. [[:w:Driving While Black|Driving While Black]]). For de Laat's study of Wikipedia profiling, "two types of complications are important: (1) possible ‘overuse’ of dimension(s) (an issue of profile effectiveness) and (2) social sensibilities associated with specific dimension(s) (a social and moral issue)." Overuse can mean relying on stereotypes that have no basis in reality, or over-reliance on some dimensions that, while having a non-spurious correlation with the deviant behavior, are over-emphasized at the expense of other relevant characteristics because they are more visible or salient to the profile. E.g. while Schauer considers that it may be justified for "airport officials looking for explosives [to] single out for inspection the luggage of younger Muslim men of Middle Eastern appearance", it would be an over-use if "officials ask ''all'' Muslim men and ''all'' men of Middle Eastern origin to step out of line to be searched", thus reducing their effectiveness by neglecting other passenger characteristics. This is also an example for the second type of complication profiling, where the selected dimensions are socially sensitive – indeed, for the specific case of luggage screening in the US, "the factors of race, religion, ethnicity, nationality, and gender have expressly been excluded from profiling" since 1997.
Next, de Laat turns to question 2, on whether vandalism profiling is also morally justified. Here he relies on later work by Schauer, from a 2003 book, "Profiles, Probabilities, and Stereotypes", that studies such matters as profiling by tax officials (selecting which taxpayers have to undergo an audit), airport security (selecting passengers for screening) and by police officers (e.g. selecting cars for traffic stops). While profiling of some kind is a necessity for all these officials, the particular characteristics (dimensions) used for profiling can be highly problematic (see e.g. [[:w:Driving While Black|Driving While Black]]). For de Laat's study of Wikipedia profiling, "two types of complications are important: (1) possible ‘overuse’ of dimension(s) (an issue of profile effectiveness) and (2) social sensibilities associated with specific dimension(s) (a social and moral issue)." Overuse can mean relying on stereotypes that have no basis in reality, or over-reliance on some dimensions that, while having a non-spurious correlation with the deviant behavior, are over-emphasized at the expense of other relevant characteristics because they are more visible or salient to the profile. E.g. while Schauer considers that it may be justified for "airport officials looking for explosives [to] single out for inspection the luggage of younger Muslim men of Middle Eastern appearance", it would be an over-use if "officials ask ''all'' Muslim men and ''all'' men of Middle Eastern origin to step out of line to be searched", thus reducing their effectiveness by neglecting other passenger characteristics. This is also an example for the second type of complication profiling, where the selected dimensions are socially sensitive – indeed, for the specific case of luggage screening in the US, "the factors of race, religion, ethnicity, nationality, and gender have expressly been excluded from profiling" since 1997.