�ݺ�ߣshows by User: ClareCorthell

�ݺ�ߣshows by User: ClareCorthell / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: ClareCorthell / Tue, 20 Sep 2016 17:30:49 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: ClareCorthell Engineering Ethics: Practicing Fairness /slideshow/engineering-ethics-practicing-fairness/66224554 bendalgoethicspost-160920173049
In AI We Trust? Ethics & Bias in Machine Learning Hosted by Seven Peaks Ventures and Fast Forward Labs September 2016 Decision-making about critical life stages (college admissions, creditworthiness, employability, jail sentencing) is rapidly becoming centralized and predicted by automated systems like machine learning models. As Data Scientists, the creators of those models, how do we take responsibility for those decisions? How do we define our goals, and how do we measure the effect? As this presents a unique opportunity and risk to businesses, we all become invested in the answers to these questions. Here, I focus on the tactical elements of measuring fairness as well as the forward-looking concerns and opportunities this paradigmatic change presents. https://www.eventbrite.com/e/in-ai-we-trust-ethics-bias-in-machine-learning-tickets-26313436196#]]>
In AI We Trust? Ethics & Bias in Machine Learning Hosted by Seven Peaks Ventures and Fast Forward Labs September 2016 Decision-making about critical life stages (college admissions, creditworthiness, employability, jail sentencing) is rapidly becoming centralized and predicted by automated systems like machine learning models. As Data Scientists, the creators of those models, how do we take responsibility for those decisions? How do we define our goals, and how do we measure the effect? As this presents a unique opportunity and risk to businesses, we all become invested in the answers to these questions. Here, I focus on the tactical elements of measuring fairness as well as the forward-looking concerns and opportunities this paradigmatic change presents. https://www.eventbrite.com/e/in-ai-we-trust-ethics-bias-in-machine-learning-tickets-26313436196#]]> Tue, 20 Sep 2016 17:30:49 GMT /slideshow/engineering-ethics-practicing-fairness/66224554 ClareCorthell@slideshare.net(ClareCorthell) Engineering Ethics: Practicing Fairness ClareCorthell In AI We Trust? Ethics & Bias in Machine Learning Hosted by Seven Peaks Ventures and Fast Forward Labs September 2016 Decision-making about critical life stages (college admissions, creditworthiness, employability, jail sentencing) is rapidly becoming centralized and predicted by automated systems like machine learning models. As Data Scientists, the creators of those models, how do we take responsibility for those decisions? How do we define our goals, and how do we measure the effect? As this presents a unique opportunity and risk to businesses, we all become invested in the answers to these questions. Here, I focus on the tactical elements of measuring fairness as well as the forward-looking concerns and opportunities this paradigmatic change presents. https://www.eventbrite.com/e/in-ai-we-trust-ethics-bias-in-machine-learning-tickets-26313436196# <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/bendalgoethicspost-160920173049-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> In AI We Trust? Ethics & Bias in Machine Learning Hosted by Seven Peaks Ventures and Fast Forward Labs September 2016 Decision-making about critical life stages (college admissions, creditworthiness, employability, jail sentencing) is rapidly becoming centralized and predicted by automated systems like machine learning models. As Data Scientists, the creators of those models, how do we take responsibility for those decisions? How do we define our goals, and how do we measure the effect? As this presents a unique opportunity and risk to businesses, we all become invested in the answers to these questions. Here, I focus on the tactical elements of measuring fairness as well as the forward-looking concerns and opportunities this paradigmatic change presents. https://www.eventbrite.com/e/in-ai-we-trust-ethics-bias-in-machine-learning-tickets-26313436196#

Engineering Ethics: Practicing Fairness from Clare Corthell

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0 Distributed Natural Language Processing Systems in Python /slideshow/distributed-natural-language-processing-systems-in-python/58827044 slidesharetmconfnlp-160228220550
Much of human knowledge is “locked up” in a type of data called text. Humans are great at reading, but are computers? This workshop leads you through open source data science libraries in Python that turn text into valuable data, then tours an open source system built for the Wordnik dictionary to source definitions of words from across the internet. Thinking Machines Conference, Manila, February 2016 http://thinkingmachin.es/events/]]>
Much of human knowledge is “locked up” in a type of data called text. Humans are great at reading, but are computers? This workshop leads you through open source data science libraries in Python that turn text into valuable data, then tours an open source system built for the Wordnik dictionary to source definitions of words from across the internet. Thinking Machines Conference, Manila, February 2016 http://thinkingmachin.es/events/]]> Sun, 28 Feb 2016 22:05:50 GMT /slideshow/distributed-natural-language-processing-systems-in-python/58827044 ClareCorthell@slideshare.net(ClareCorthell) Distributed Natural Language Processing Systems in Python ClareCorthell Much of human knowledge is “locked up” in a type of data called text. Humans are great at reading, but are computers? This workshop leads you through open source data science libraries in Python that turn text into valuable data, then tours an open source system built for the Wordnik dictionary to source definitions of words from across the internet. Thinking Machines Conference, Manila, February 2016 http://thinkingmachin.es/events/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/slidesharetmconfnlp-160228220550-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Much of human knowledge is “locked up” in a type of data called text. Humans are great at reading, but are computers? This workshop leads you through open source data science libraries in Python that turn text into valuable data, then tours an open source system built for the Wordnik dictionary to source definitions of words from across the internet. Thinking Machines Conference, Manila, February 2016 http://thinkingmachin.es/events/

Distributed Natural Language Processing Systems in Python from Clare Corthell

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0 Hybrid Intelligence: The New Paradigm /slideshow/hybrid-intelligence-the-new-paradigm/58826792 slidesharetmconfhybrid2-160228215400
[The full content of this talk can be found in this article: https://medium.com/@clarecorthell/hybrid-artificial-intelligence-how-artificial-assistants-work-eefbafbd5334] When we think about automated, learning systems, we often think of a world without humans - but there are many signs and limitations that show we’re not moving toward a human-free world. We’ll explore the strengths and weaknesses of humans and computers, and explore the new design paradigm that’s making artificial intelligence more powerful than it’s ever been before. Thinking Machines Conference, February 2016, Manila http://thinkingmachin.es/events/]]>
[The full content of this talk can be found in this article: https://medium.com/@clarecorthell/hybrid-artificial-intelligence-how-artificial-assistants-work-eefbafbd5334] When we think about automated, learning systems, we often think of a world without humans - but there are many signs and limitations that show we’re not moving toward a human-free world. We’ll explore the strengths and weaknesses of humans and computers, and explore the new design paradigm that’s making artificial intelligence more powerful than it’s ever been before. Thinking Machines Conference, February 2016, Manila http://thinkingmachin.es/events/]]> Sun, 28 Feb 2016 21:54:00 GMT /slideshow/hybrid-intelligence-the-new-paradigm/58826792 ClareCorthell@slideshare.net(ClareCorthell) Hybrid Intelligence: The New Paradigm ClareCorthell [The full content of this talk can be found in this article: https://medium.com/@clarecorthell/hybrid-artificial-intelligence-how-artificial-assistants-work-eefbafbd5334] When we think about automated, learning systems, we often think of a world without humans - but there are many signs and limitations that show we’re not moving toward a human-free world. We’ll explore the strengths and weaknesses of humans and computers, and explore the new design paradigm that’s making artificial intelligence more powerful than it’s ever been before. Thinking Machines Conference, February 2016, Manila http://thinkingmachin.es/events/ <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/slidesharetmconfhybrid2-160228215400-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> [The full content of this talk can be found in this article: https://medium.com/@clarecorthell/hybrid-artificial-intelligence-how-artificial-assistants-work-eefbafbd5334] When we think about automated, learning systems, we often think of a world without humans - but there are many signs and limitations that show we’re not moving toward a human-free world. We’ll explore the strengths and weaknesses of humans and computers, and explore the new design paradigm that’s making artificial intelligence more powerful than it’s ever been before. Thinking Machines Conference, February 2016, Manila http://thinkingmachin.es/events/

Hybrid Intelligence: The New Paradigm from Clare Corthell

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0 Scaling Harm: Designing Artificial Intelligence for Humans /ClareCorthell/designing-artificial-intelligence-for-humans wrangleslideshare-151024174145-lva1-app6891
On the responsibility of creators of inference algorithms to people in the real world (Wrangle 2015) Video: bit.ly/scalingharmvideo]]>
On the responsibility of creators of inference algorithms to people in the real world (Wrangle 2015) Video: bit.ly/scalingharmvideo]]> Sat, 24 Oct 2015 17:41:45 GMT /ClareCorthell/designing-artificial-intelligence-for-humans ClareCorthell@slideshare.net(ClareCorthell) Scaling Harm: Designing Artificial Intelligence for Humans ClareCorthell On the responsibility of creators of inference algorithms to people in the real world (Wrangle 2015) Video: bit.ly/scalingharmvideo <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/wrangleslideshare-151024174145-lva1-app6891-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> On the responsibility of creators of inference algorithms to people in the real world (Wrangle 2015) Video: bit.ly/scalingharmvideo

Scaling Harm: Designing Artificial Intelligence for Humans from Clare Corthell

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0 https://cdn.slidesharecdn.com/profile-photo-ClareCorthell-48x48.jpg?cb=1530322459 clarecorthell.org https://cdn.slidesharecdn.com/ss_thumbnails/bendalgoethicspost-160920173049-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/engineering-ethics-practicing-fairness/66224554 Engineering Ethics: Pr... https://cdn.slidesharecdn.com/ss_thumbnails/slidesharetmconfnlp-160228220550-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/distributed-natural-language-processing-systems-in-python/58827044 Distributed Natural La... https://cdn.slidesharecdn.com/ss_thumbnails/slidesharetmconfhybrid2-160228215400-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/hybrid-intelligence-the-new-paradigm/58826792 Hybrid Intelligence: T...