{"id":"https://openalex.org/W2740461713","doi":"https://doi.org/10.18653/v1/w17-1611","title":"Goal-Oriented Design for Ethical Machine Learning and NLP","display_name":"Goal-Oriented Design for Ethical Machine Learning and NLP","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2740461713","doi":"https://doi.org/10.18653/v1/w17-1611","mag":"2740461713"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w17-1611","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-1611","pdf_url":"https://www.aclweb.org/anthology/W17-1611.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the First ACL Workshop on Ethics in Natural Language Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W17-1611.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013200803","display_name":"Tyler Schnoebelen","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tyler Schnoebelen","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5013200803"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4033,"has_fulltext":true,"cited_by_count":6,"citation_normalized_percentile":{"value":0.7161421,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"88","last_page":"93"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10883","display_name":"Ethics and Social Impacts of AI","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/3311","display_name":"Safety Research"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9435999989509583,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13051","display_name":"Qualitative Comparative Analysis Research","score":0.92330002784729,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/argument","display_name":"Argument (complex analysis)","score":0.8073298335075378},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6849632859230042},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6749057769775391},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.6413187980651855},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.49522724747657776},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.4721015989780426},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.46109071373939514}],"concepts":[{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.8073298335075378},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6849632859230042},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6749057769775391},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.6413187980651855},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49522724747657776},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4721015989780426},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.46109071373939514},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w17-1611","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-1611","pdf_url":"https://www.aclweb.org/anthology/W17-1611.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the First ACL Workshop on Ethics in Natural Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w17-1611","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-1611","pdf_url":"https://www.aclweb.org/anthology/W17-1611.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the First ACL Workshop on Ethics in Natural Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6600000262260437,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2740461713.pdf","grobid_xml":"https://content.openalex.org/works/W2740461713.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W64581525","https://openalex.org/W391275746","https://openalex.org/W623900253","https://openalex.org/W1515810707","https://openalex.org/W1593687854","https://openalex.org/W1605760667","https://openalex.org/W1990921190","https://openalex.org/W1993044894","https://openalex.org/W2001498083","https://openalex.org/W2004679316","https://openalex.org/W2010793828","https://openalex.org/W2056224157","https://openalex.org/W2066545696","https://openalex.org/W2143596091","https://openalex.org/W2163284576","https://openalex.org/W2552893417","https://openalex.org/W2566203197","https://openalex.org/W2591282543","https://openalex.org/W2797784986","https://openalex.org/W2899570017","https://openalex.org/W3098567718","https://openalex.org/W3126349953","https://openalex.org/W3128719370","https://openalex.org/W4243160567","https://openalex.org/W4249292692","https://openalex.org/W4298832141","https://openalex.org/W4301056702","https://openalex.org/W4320476029"],"related_works":["https://openalex.org/W3008380943","https://openalex.org/W2115206405","https://openalex.org/W4387718383","https://openalex.org/W1528986568","https://openalex.org/W2500746363","https://openalex.org/W2062799661","https://openalex.org/W2347954438","https://openalex.org/W2071460425","https://openalex.org/W2946506623","https://openalex.org/W2170067308"],"abstract_inverted_index":{"The":[0,44,65],"argument":[1],"made":[2],"in":[3,11,84],"this":[4],"paper":[5,45,66],"is":[6,67],"that":[7,26,33,53,81],"to":[8,69,95],"act":[9],"ethically":[10],"machine":[12],"learning":[13],"and":[14,63,76],"NLP":[15,20],"requires":[16],"focusing":[17],"on":[18,74,93],"goals.":[19],"projects":[21],"are":[22,82],"often":[23],"classificatory":[24],"systems":[25,40],"deal":[27],"with":[28],"human":[29],"subjects,":[30],"which":[31],"means":[32],"goals":[34],"from":[35],"people":[36],"affected":[37],"by":[38],"the":[39,57,70,77],"should":[41],"be":[42],"included.":[43],"takes":[46],"as":[47],"its":[48],"core":[49],"example":[50],"a":[51],"model":[52],"detects":[54],"criminality,":[55],"showing":[56],"problems":[58],"of":[59,72,79],"training":[60],"data,":[61],"categories,":[62],"outcomes.":[64],"oriented":[68],"kinds":[71],"critiques":[73],"power":[75],"reproduction":[78],"inequality":[80],"found":[83],"social":[85],"theory,":[86],"but":[87],"it":[88],"also":[89],"includes":[90],"concrete":[91],"suggestions":[92],"how":[94],"put":[96],"goal-oriented":[97],"design":[98],"into":[99],"practice.":[100]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}