general

https://codesachin.wordpress.com/2017/01/05/on-interpretable-models/
https://www.oreilly.com/learning/introduction-to-local-interpretable-model-agnostic-explanations-lime
https://www.oreilly.com/ideas/ideas-on-interpreting-machine-learning
https://dataskeptic.com/blog/transcripts/2016/trusting-machine-learning-models-with-lime
https://shiring.github.io/machine_learning/2017/04/23/one_r
https://www.r-bloggers.com/explaining-complex-machine-learning-models-with-lime/
https://thecrimereport.org/2018/01/26/algorithms-and-justice-scrapping-the-black-box/
https://www.cmu.edu/news/stories/archives/2018/october/explainable-ai.html
http://www.imm.dtu.dk/~tobo/AI_chora2.pdf
https://journal.jp.fujitsu.com/en/2018/10/11/01/
https://link.springer.com/content/pdf/10.1007%2Fs00287-018-1102-5.pdf
https://www.parc.com/blog/explainable-ai-an-overview-of-parcs-cogle-project-with-darpa/
https://bdtechtalks.com/2018/10/15/kate-saenko-explainable-ai-deep-learning-rise/
https://www.ribbonfarm.com/2018/03/13/justifiable-ai/
https://pursuit.unimelb.edu.au/articles/what-were-you-thinking
https://which-50.com/autonomous-cars-present-new-challenges-for-explainable-ai/
https://tech.co/sexist-ai-doomed-reflect-worst-2018-10
https://www.cmo.com.au/article/648282/why-explainability-around-ai-gaining-ground/
https://www.kdnuggets.com/2018/10/enterprise-explainable-ai.html
https://www.research.ox.ac.uk/Article/2018-10-15-making-algorithms-accountable-and-explainable-the-need-for-a-legal-framework
https://which-50.com/autonomous-cars-present-new-challenges-for-explainable-ai/
https://www.hfsresearch.com/pointsofview/escape-the-black-box-take-steps-toward-explainable-ai-today-or-risk-damaging-your-business
https://ercim-news.ercim.eu/en112/r-i/can-we-trust-machine-learning-results-artificial-intelligence-in-safety-critical-decision-support
https://research.utwente.nl/en/publications/automated-failure-diagnosis-in-aviation-maintenance-using-explain
https://blogs.wsj.com/cio/tag/explainable-ai/
https://blog.goodaudience.com/holy-grail-of-ai-for-enterprise-explainable-ai-xai-6e630902f2a0
https://www.infosecurity-magazine.com/news/orgs-failing-tmachine-learning/
https://www.turing.ac.uk/news/can-justice-be-blind-when-it-comes-machine-learning
https://blog.acolyer.org/2018/08/13/delayed-impact-of-fair-machine-learning/
https://fairmlbook.org
https://www.linkedin.com/pulse/why-machine-learning-model-interpretability-big-deal-igor-korolev/
http://www.fatml.org
https://www.oreilly.com/ideas/why-its-hard-to-design-fair-machine-learning-models?utm_medium=social&utm_source=twitter.com&utm_campaign=awareness&utm_content=radar+content
https://christophm.github.io/interpretable-ml-book/intro.html
http://blog.datadive.net/interpreting-random-forests/
https://xai.world
https://medium.com/@BonsaiAI/explainable-ai-3-deep-explanations-approaches-to-xai-1807e251e537
https://towardsdatascience.com/decision-trees-understanding-explainable-ai-620fc37e598d
https://www.fico.com/blogs/analytics-optimization/4-analytic-predictions-for-2017/
https://hci-kdd.org/2017/10/09/transparency-trust-machine-learning-making-ai-interpretable-explainable/
https://www.nytimes.com/2017/11/21/magazine/can-ai-be-taught-to-explain-itself.html
https://www.linkedin.com/pulse/explainable-ai-understanding-black-box-machine-learning-singh/
http://www.sciencemag.org/news/2017/07/how-ai-detectives-are-cracking-open-black-box-deep-learning
https://blog.foretellix.com/2016/08/31/machine-learning-verification-and-explainable-ai/
https://trustable.ai/gdpr-impacts-machine-learning-applications/
https://www.cio.com/article/3234305/privacy/eu-privacy-law-says-companies-need-to-explain-the-algorithms-they-use.html
https://gdpr.report/news/2017/08/23/deep-learning-not-ai-future/
https://medium.com/trustableai/gdpr-and-its-impacts-on-machine-learning-applications-d5b5b0c3a815
https://simmachines.com/explainable-ai-is-responsible-ai/
https://www.it-finanzmagazin.de/xai-wissen-was-die-ki-wirklich-macht-kuenstliche-intelligenz-erklaerbar-67609/
https://blogs.wsj.com/cio/2016/12/06/capital-one-pursues-explainable-ai-to-guard-against-bias-in-models/
https://blogs.wsj.com/cio/2018/05/02/companies-grapple-with-ais-opaque-decision-making-process/
https://blogs.wsj.com/cio/2017/08/11/the-morning-download-darpa-orchestrates-effort-to-make-ai-explain-itself/
https://blogs.wsj.com/cio/2017/10/26/facing-growing-concern-over-ai-tech-firms-call-for-responsible-development/
https://blogs.wsj.com/cio/2017/08/10/inside-darpas-push-to-make-artificial-intelligence-explain-itself/
https://www.groundai.com/project/explanations-of-model-predictions-with-live-and-breakdown-packages/
https://lilianweng.github.io/lil-log/2017/08/01/how-to-explain-the-prediction-of-a-machine-learning-model.html#prediction-decomposition
https://pbiecek.github.io/DALEX_docs/index.html#introduction
https://pbiecek.github.io/breakDown/articles/break_caret.html
https://www.linkedin.com/pulse/explainable-ai-implications-compliance-gdpr-beyond-scott-zoldi/
https://towardsdatascience.com/human-interpretable-machine-learning-part-1-the-need-and-importance-of-model-interpretation-2ed758f5f476
https://www.oreilly.com/ideas/interpreting-predictive-models-with-skater-unboxing-model-opacity
https://www.technologyreview.com/s/604087/the-dark-secret-at-the-heart-of-ai/
http://danshiebler.com/2017-04-16-deep-taylor-lrp/
http://www.sciencemag.org/news/2017/07/how-ai-detectives-are-cracking-open-black-box-deep-learning
https://www.wired.com/story/why-ai-is-still-waiting-for-its-ethics-transplant/
https://venturebeat.com/2018/05/21/explainable-ai-could-reduce-the-impact-of-biased-algorithms/
https://optimizingmind.com/explainable-ai-demonstration/
https://www.economist.com/science-and-technology/2018/02/15/for-artificial-intelligence-to-thrive-it-must-explain-itself
https://hbr.org/2013/04/the-hidden-biases-in-big-data
https://www.nytimes.com/2017/11/21/magazine/can-ai-be-taught-to-explain-itself.html
https://www.wired.com/2016/04/google-ensures-services-almost-never-go/?mbid=nl_4616
https://www.computerworld.com.au/article/621059/google-research-chief-questions-value-explainable-ai/
https://www.delltechnologies.com/en-us/perspectives/explainable-ai-cracking-open-deep-learnings-black-box/
https://simplystatistics.org/2017/07/10/the-machines-learn-but-we-don-t/
https://www.weforum.org/agenda/2017/10/we-need-to-overcome-ais-inherent-human-bias/
https://www.axios.com/why-good-ai-needs-to-be-able-to-show-its-work-f360b149-b199-4f49-90ea-de16d9b4cd8b.html
https://www.forbes.com/sites/paulhsieh/2017/05/22/3-big-questions-about-ai-guided-medicine/#703267874f20
https://www.politico.com/newsletters/morning-ehealth/2018/05/01/ata-sees-physician-burnout-as-a-telemedicine-opportunity-199148
http://www.thefuturesociety.org/ethical-policy-risks-of-artificial-intelligence-in-healthcare/
https://www.oii.ox.ac.uk/blog/could-counterfactuals-explain-algorithmic-decisions-without-opening-the-black-box/
http://www.spiegel.de/netzwelt/web/explainable-ai-auf-der-cebit-2018-wie-tickt-eine-kuenstliche-intelligenz-a-1213016.html
https://medium.com/@eirinimalliaraki/toward-ethical-transparent-and-fair-ai-ml-a-critical-reading-list-d950e70a70ea
https://www.prnewswire.com/news-releases/partners-connected-health-and-hitachi-develop-an-explainable-ai-technology-to-help-doctors-predict-readmissions-and-improve-patient-outcomes-300570129.html
https://www.accenture.com/us-en/blogs/blogs-why-explainable-ai-must-central-responsible-ai
https://ai.intel.com/the-challenges-and-opportunities-of-explainable-ai/
https://connectedsocialmedia.com/16336/increasing-trust-in-ai-systems-through-explainability-intel-chip-chat-episode-573/
https://www.bbc.com/news/business-44466213
https://futureoflife.org/2018/02/13/transparent-interpretable-ai/?cn-reloaded=1
https://www.endgame.com/blog/technical-blog/prove-it-2018-wave-information-security-machine-learning
https://www.kdnuggets.com/2015/04/model-interpretability-neural-networks-deep-learning.html
https://www.mobihealthnews.com/content/optum-research-head-describes-ais-black-box-problem-and-its-impact-healthcare?mkt_tok=eyJpIjoiWlRBME5EQmtZak5sWldFMiIsInQiOiI2RjRxbHpcL25PQkxJQ3NENDYxR2hDTG5vVWdkOFB6cHh2NEpMN2ZCQWZEQmRkMHVIWDVyZWVKejRJb09Sa1kyeG9aaXhQQjdZWjMyNVwva2VjWGg2TmJwR2N2VFNJcms0a3VcL1FDQ2R1Mm96dUdvN25HWFNHamFlamdlK3lmQlhrNyJ9
https://medium.com/applied-data-science/new-r-package-the-xgboost-explainer-51dd7d1aa211
http://www.markstefik.com/?page_id=2262
http://web.engr.oregonstate.edu/~afern/
https://www.wired.com/story/why-ai-is-still-waiting-for-its-ethics-transplant/
http://openaccess.city.ac.uk/18660/
https://datafloq.com/read/algorithms-black-boxes-need-explainable-AI/2639
https://hbr.org/2018/05/how-health-care-changes-when-algorithms-start-making-diagnoses
https://disruptionhub.com/next-big-disruptive-trend-business-explainable-ai/
https://www.wsj.com/articles/career-of-the-future-robot-psychologist-1499605203
https://web.cs.ucla.edu/~guyvdb/code/
https://blog.fastforwardlabs.com/2017/03/09/fairml-auditing-black-box-predictive-models.html
http://uc-r.github.io/dalex#local
https://www.washingtontimes.com/news/2018/jun/29/darpas-explainable-ai-a-common-sense-comfort-in-a-/
https://www.tractica.com/artificial-intelligence/explainable-ai-and-its-impact-on-ai-adoption/
https://www.business-science.io/business/2018/07/23/dalex-feature-interpretation.html
https://www.analyticsvidhya.com/blog/2017/06/building-trust-in-machine-learning-models/
https://blog.godatadriven.com/fairness-in-ml
https://blog.godatadriven.com/fairness-in-pytorch
https://people.csail.mit.edu/beenkim/papers/BeenK_FinaleDV_ICML2017_tutorial.pdf
https://thenextweb.com/artificial-intelligence/2018/09/12/mit-taught-a-neural-network-how-to-show-its-work/
https://github.com/yashpatel5400/interpretability
https://github.com/jphall663/awesome-machine-learning-interpretability
https://github.com/dongyp13/Robust-and-Explainable-Machine-Learning#interpretability
https://github.com/liupeng3425/interpretable-research
https://github.com/grazianomita/Model-Interpretability
https://github.com/dongyp13/Robust-and-Explainable-Machine-Learning#interpretability
https://law.yale.edu/system/files/area/center/isp/documents/law_and_artificial_intelligence_reading_group_syllabus-spring2018.pdf
https://www.analyticsvidhya.com/blog/2019/03/datahack-radio-interpretable-machine-learning-christoph-molnar/
https://singularityhub.com/2019/03/19/to-be-ethical-ai-must-become-explainable-how-do-we-get-there/#sm.0001pbmwwl82udh2ylz1ha6wqnrgu
https://www.forbes.com/sites/adrianbridgwater/2019/03/22/will-ai-cheats-outsmart-us/#10161802448f
https://www.lendacademy.com/podcast-192-douglas-merrill-of-zestfinance/
http://digitalhealthage.com/are-we-ready-for-radiologists-powered-by-ai-and-mistakes/
https://medium.com/predict/can-we-build-an-artificial-brain-network-using-nanoscale-magnets-1c0a925973ab
https://www.forbes.com/sites/tomdavenport/2019/03/18/explainable-ai-and-the-rebirth-of-rules/#17764fb439ae
https://users.cs.duke.edu/~cynthia/code.html
https://thecrimereport.org/2018/01/26/algorithms-and-justice-scrapping-the-black-box/
https://towardsdatascience.com/machine-learning-interpretability-techniques-662c723454f3
https://opendatascience.com/explainable-ai-from-prediction-to-understanding/
https://aibusiness.com/explainability-ai-regulation/
https://www.heinz.cmu.edu/media/2018/September/explainable-ai
https://www.the-future-of-commerce.com/2019/03/11/what-is-explainable-ai-xai/
https://www.capitalone.com/tech/machine-learning/an-integral-pragmatic-approach-to-explainable-ai
https://towardsdatascience.com/how-to-explain-any-machine-learning-model-prediction-30654b0c1c8
https://tech.economictimes.indiatimes.com/news/corporate/digite-aims-to-improve-it-services-firms-margin-using-explainable-ai-tool/68416528
https://insidehpc.com/2019/03/any-better-than-clever-hans-putting-ai-systems-to-the-test/
https://www.analyticsinsight.net/here-is-how-augmented-analytics-and-explainable-ai-will-cause-a-disruption-in-2019-beyond/
https://www.darpa.mil/news-events/2019-01-31
https://www.governmentciomedia.com/machine-learning-creating-crisis-science
https://arxiv.org/abs/1902.11035v1
https://github.com/ModelOriented/SAFE
https://milbankmonitor.com/the-security-threats-of-neural-networks-and-deep-learning-algorithms/28/02/2019/
https://redtailmedia.org/2018/10/29/a-peek-inside-a-darpa-xai-project-at-oregon-state-university/
https://ethical.institute/mle/12.html
https://medium.com/capital-one-tech/advancing-greater-fairness-and-explainability-for-ai-and-machine-learning-across-the-banking-6a71423476fe
https://www.proshareng.com/news/Tech%20Trends/An-Overview-of-AI-for-Wealth-Management-%E2%80%93-What%E2%80%99s-Possible-Today/43270
https://ctmfile.com/story/bi-2019-explainable-ai-natural-language-to-humanize-your-data-etc
https://thenewstack.io/explainable-ai-looking-into-the-black-box/
https://www.basistech.com/honest-ai/understanding-explainable-ai/
http://www.project-pulse.eu/using-ai-with-explainable-deep-learning-to-help-save-lives/
https://github.com/EthicalML/XAI
https://notepad.mmakowski.com/Tech/KDD%202018:%20Explainable%20Models%20for%20Healthcare%20AI
http://www.stat.ucla.edu/~tfwu//project_posts/iRCNN/
https://github.com/jphall663/awesome-machine-learning-interpretability
https://github.com/ankitbit/MAGMIL
https://github.com/zzzace2000/FIDO-saliency
https://github.com/antoinecarme/sklearn_explain
https://arxiv.org/abs/1711.04574
https://towardsdatascience.com/deepmind-combines-logic-and-neural-networks-to-extract-rules-from-noisy-data-2fbd0f6edfb7
https://arxiv.org/abs/1902.01876v1
https://sites.google.com/view/xai2019/home
https://venturebeat.com/2019/03/06/openai-and-google-detail-activation-atlases-a-technique-for-visualizing-ai-decision-making/
https://towardsdatascience.com/why-model-explainability-is-the-next-data-science-superpower-b11b6102a5e0
https://towardsdatascience.com/interpretable-ai-or-how-i-learned-to-stop-worrying-and-trust-ai-e61f9e8ee2c2
https://towardsdatascience.com/google-and-openai-help-you-see-what-neural-networks-see-77ec5fd9564a
https://www.geopoliticalmonitor.com/in-search-of-explainable-artificial-intelligence/
https://towardsdatascience.com/how-to-perform-explainable-machine-learning-classification-without-any-trees-873db4192c68
https://bdtechtalks.com/2019/03/11/openai-google-neural-networks-visualization/
https://www.analyticsindiamag.com/explainable-ai-is-driving-the-credit-analytics-market-now-says-mathieu-garnier-of-equifax/?
https://towardsdatascience.com/understand-how-your-tensorflow-model-is-making-predictions-d0b3c7e88500
https://www.linkedin.com/pulse/data-science-analytics-informatics-healthcare-life-korolev-do-phd/
https://www.sciencedaily.com/releases/2019/03/190312103643.htm
https://bdtechtalks.com/2019/01/10/darpa-xai-explainable-artificial-intelligence/
https://www.quantamagazine.org/been-kim-is-building-a-translator-for-artificial-intelligence-20190110/
http://www.sys-con.com/node/4367298
https://www.itproportal.com/features/cutting-through-the-ai-hype-explainable-ai-and-a-flexible-workforce/
https://www.forbes.com/sites/forbestechcouncil/2019/01/15/five-predictions-for-ai-in-marketing-in-2019/#8c10cff7efa6
https://phys.org/news/2019-01-ai-retailers-consumer.html
https://github.com/marcoancona/DeepExplain
https://github.com/tensorflow/tcav/
https://github.com/albermax/innvestigate
https://github.com/nyuvis/explanation_explorer
https://www.theverge.com/2019/1/17/18186674/daniel-chen-machine-learning-rule-of-law-economics-psychology-judicial-system-policy
https://venturebeat.com/2019/01/26/mit-csail-researchers-propose-automated-method-for-debiasing-ai-algorithms/
https://www.cnbc.com/2019/01/23/facebook-samsung-engineers-quit-to-form-ai-startup-fiddler-labs.html
https://www.brighttalk.com/webcast/16463/346891
https://www.vox.com/science-and-health/2019/1/23/18194717/alexandria-ocasio-cortez-ai-bias
https://www.mesalliance.org/2019/01/25/microstrategy-ai-strategies-becoming-a-necessity-more-explainable-ai-are-among-top-2019-trends-to-watch/
http://virtual-strategy.com/2019/01/23/executive-viewpoint-2019-prediction-tigergraph-big-data-analytics-and-explainable-ai/
https://www.zdnet.com/article/artificial-intelligence-will-become-the-next-new-human-right/
https://arxiv.org/html/1901.08813v1
https://www.mesalliance.org/2019/01/22/ai-2018-the-year-of-citizen-ai/
http://mil-embedded.com/news/charles-river-analytics-creates-tool-to-help-ai-communicate-effectively-with-humans/
https://www.timesofmalta.com/articles/view/20190120/life-features/explainable-ai.699695
https://www.nytimes.com/2017/12/20/upshot/algorithms-bail-criminal-justice-system.html
https://www.washingtonpost.com/gdpr-consent/?destination=%2fnews%2fmonkey-cage%2fwp%2f2016%2f10%2f17%2fcan-an-algorithm-be-racist-our-analysis-is-more-cautious-than-propublicas%2f%3fnoredirect%3don%26utm_term%3d.51e7d4145743&noredirect=on&utm_term=.7e8111db903c
https://www.cmswire.com/digital-workplace/ai-adoption-is-increasing-but-challenges-remain/
https://slides.com/ahmadadiga/session1-10-13-15-22-30-7-13-23#/
https://arxiv.org/abs/1902.00006v1
https://www.businesswire.com/news/home/20190204005511/en/Lazard-Add-Explainable-Artificial-Intelligence-XAI-Capability
https://bdtechtalks.com/2019/02/04/explainable-ai-gan-dissection-ibm-mit/
https://readwrite.com/2019/02/05/ai-should-be-reducing-bias-not-introducing-it-in-recruiting/
https://betanews.com/2019/02/05/rise-of-explainable-ai/
https://sdtimes.com/ai/can-developers-make-ais-black-box-transparent/
https://www.forbes.com/sites/forbestechcouncil/2019/02/07/why-you-should-or-should-not-trust-ai/#66cfebd8646f
https://www.meritalk.com/articles/when-the-stakes-are-high-will-people-trust-ai/
https://www.techcircle.in/2019/02/18/augmented-analytics-explainable-ai-have-potential-for-disruption-gartner
http://www.bankingexchange.com/news-feed/item/7785-why-explainable-ai-is-the-next-frontier-in-financial-crime-fighting?Itemid=259
http://www.cxotoday.com/story/gartner-identifies-top-10-data-and-analytics-technology-trends-for-2019/
https://arxiv.org/abs/1902.03501v1
https://www.dataiq.co.uk/articles/symptoms-and-solutions-to-machine-learning-bias
https://blogs.wsj.com/cio/tag/explainable-ai/
https://www.oreilly.com/ideas/ideas-on-interpreting-machine-learning
https://www.oreilly.com/learning/introduction-to-local-interpretable-model-agnostic-explanations-lime
https://blog.goodaudience.com/holy-grail-of-ai-for-enterprise-explainable-ai-xai-6e630902f2a0
http://www.heatmapping.org/
https://arxiv.org/abs/1711.06104
https://www.linkedin.com/pulse/ai-silvie-spreeuwenberg/
https://www.computer.org/csdl/proceedings-article/hicss/2005/22680243a/12OmNvSKNOs
http://www.cs.tau.ac.il/~wolf/papers/a_formal_approach_to_explainability.pdf
https://www.nytimes.com/2018/01/25/opinion/artificial-intelligence-black-box.html
http://www.imm.dtu.dk/~tobo/AI_chora2.pdf
http://cdn.bdigital.org/PDF/BDC18/BDC18_ExplainableAI.pdf
http://aitechnologylaw.com/2018/12/explainable-ai-crucial-in-this-area-of-law/
https://www.meritalk.com/articles/ethics-a-crucial-link-in-dods-ai-strategy/
https://www.law360.com/lifesciences/articles/1131225/explainability-where-ai-and-liabilihttps://www.technative.io/why-its-important-to-create-a-movement-around-explainable-ai/
ty-meet
https://towardsdatascience.com/machine-learning-explainability-d6a3d198fd95
https://www.kaggle.com/learn/machine-learning-explainability
https://www.forbes.com/sites/forbestechcouncil/2019/02/22/explainable-ai-why-we-need-to-open-the-black-box/#721ef9e81717https://www.forbes.com/sites/cognitiveworld/2018/12/20/geoff-hinton-dismissed-the-need-for-explainable-ai-8-experts-explain-why-hes-wrong/#1d07df96756d
https://arxiv.org/html/1901.08813v2
https://tdwi.org/articles/2018/11/26/adv-all-3-signs-of-a-good-ai-model.aspx
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