From b67871590c21a09dd0132b209399c99720eaae3a Mon Sep 17 00:00:00 2001 From: Thoogend1 Date: Tue, 12 Jul 2022 13:07:00 +0200 Subject: [PATCH 1/2] Small punctuation cleanup --- 1-Introduction/02-ethics/README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/1-Introduction/02-ethics/README.md b/1-Introduction/02-ethics/README.md index 24fe603c..5f568a59 100644 --- a/1-Introduction/02-ethics/README.md +++ b/1-Introduction/02-ethics/README.md @@ -12,7 +12,7 @@ Market trends tell us that by 2022, 1-in-3 large organizations will buy and sell Trends also indicate that we will create and consume over [180 zettabytes](https://www.statista.com/statistics/871513/worldwide-data-created/) of data by 2025. As **Data Scientists**, this gives us unprecedented levels of access to personal data. This means we can build behavioral profiles of users and influence decision-making in ways that create an [illusion of free choice](https://www.datasciencecentral.com/profiles/blogs/the-illusion-of-choice) while potentially nudging users towards outcomes we prefer. It also raises broader questions on data privacy and user protections. -Data ethics are now _necessary guardrails_ for data science and engineering, helping us minimize potential harms and unintended consequences from our data-driven actions. The [Gartner Hype Cycle for AI](https://www.gartner.com/smarterwithgartner/2-megatrends-dominate-the-gartner-hype-cycle-for-artificial-intelligence-2020/) identifies relevant trends in digital ethics, responsible AI ,and AI governance as key drivers for larger megatrends around _democratization_ and _industrialization_ of AI. +Data ethics are now _necessary guardrails_ for data science and engineering, helping us minimize potential harms and unintended consequences from our data-driven actions. The [Gartner Hype Cycle for AI](https://www.gartner.com/smarterwithgartner/2-megatrends-dominate-the-gartner-hype-cycle-for-artificial-intelligence-2020/) identifies relevant trends in digital ethics, responsible AI, and AI governance as key drivers for larger megatrends around _democratization_ and _industrialization_ of AI. ![Gartner's Hype Cycle for AI - 2020](https://images-cdn.newscred.com/Zz1mOWJhNzlkNDA2ZTMxMWViYjRiOGFiM2IyMjQ1YmMwZQ==) @@ -84,7 +84,7 @@ The moral questions we need to ask are: #### 2.2 Informed Consent -[Informed consent](https://legaldictionary.net/informed-consent/) defines the act of users agreeing to an action (like data collection) with a _full understanding_ of relevant facts including the purpose, potential risks ,and alternatives. +[Informed consent](https://legaldictionary.net/informed-consent/) defines the act of users agreeing to an action (like data collection) with a _full understanding_ of relevant facts including the purpose, potential risks, and alternatives. Questions to explore here are: * Did the user (data subject) give permission for data capture and usage? @@ -242,7 +242,7 @@ Examples of data protection and privacy regulations: ### 4. Ethics Culture -Note that there remains an intangible gap between _compliance_ (doing enough to meet "the letter of the law") and addressing [systemic issues](https://www.coursera.org/learn/data-science-ethics/home/week/4) (like ossification, information asymmetry ,and distributional unfairness) that can speed up the weaponization of AI. +Note that there remains an intangible gap between _compliance_ (doing enough to meet "the letter of the law") and addressing [systemic issues](https://www.coursera.org/learn/data-science-ethics/home/week/4) (like ossification, information asymmetry, and distributional unfairness) that can speed up the weaponization of AI. The latter requires [collaborative approaches to defining ethics cultures](https://towardsdatascience.com/why-ai-ethics-requires-a-culture-driven-approach-26f451afa29f) that build emotional connections and consistent shared values _across organizations_ in the industry. This calls for more [formalized data ethics cultures](https://www.codeforamerica.org/news/formalizing-an-ethical-data-culture/) in organizations - allowing _anyone_ to [pull the Andon cord](https://en.wikipedia.org/wiki/Andon_(manufacturing)) (to raise ethics concerns early in the process) and making _ethical assessments_ (e.g., in hiring) a core criteria team formation in AI projects. From 68c6eb212d291d14877b45ee9d0313afdb685967 Mon Sep 17 00:00:00 2001 From: Thoogend1 Date: Wed, 13 Jul 2022 15:20:28 +0200 Subject: [PATCH 2/2] Small spelling and linkage cleanup --- .../01-defining-data-science/translations/README.es.md | 2 +- .../01-defining-data-science/translations/assignment.nl.md | 2 +- 1-Introduction/02-ethics/translations/README.ko.md | 2 +- translations/README.nl.md | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/1-Introduction/01-defining-data-science/translations/README.es.md b/1-Introduction/01-defining-data-science/translations/README.es.md index a29ab89d..c0f470dc 100644 --- a/1-Introduction/01-defining-data-science/translations/README.es.md +++ b/1-Introduction/01-defining-data-science/translations/README.es.md @@ -1,6 +1,6 @@ # Definiendo la ciencia de datos -| ![ Boceto por [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/01-Definitions.png) | +| ![ Boceto por [(@sketchthedocs)](https://sketchthedocs.dev) ](../../../sketchnotes/01-Definitions.png) | | :----------------------------------------------------------------------------------------------------: | | Definiendo la ciencia de datos - Boceto por [@nitya](https://twitter.com/nitya)_ | diff --git a/1-Introduction/01-defining-data-science/translations/assignment.nl.md b/1-Introduction/01-defining-data-science/translations/assignment.nl.md index f670798a..4474ec05 100644 --- a/1-Introduction/01-defining-data-science/translations/assignment.nl.md +++ b/1-Introduction/01-defining-data-science/translations/assignment.nl.md @@ -30,4 +30,4 @@ Vul de volgende tabel in (vul je eigen onderwerp in, indien nodig): Uitstekend | Adequaat | Vereist verbetering --- | --- | -- | -Men kon voldoende databronnen vinden, deze juist opslaan en hier de juiste inzichten aan ontlenen voor alle probleemstellingen. | Sommige aspecten van de oplssing zijn niet concreet, de data opslag is niet gedefinieerd, tenminste 2 van de probleemstellingen zijn besproken. | Enkel onderdelen vand e oplossing zijn beschreven, slechts een van de probleemstellingen is besproken. +Men kon voldoende databronnen vinden, deze juist opslaan en hier de juiste inzichten aan ontlenen voor alle probleemstellingen. | Sommige aspecten van de oplssing zijn niet concreet, de data opslag is niet gedefinieerd, tenminste 2 van de probleemstellingen zijn besproken. | Enkele onderdelen van de oplossing zijn beschreven, slechts een van de probleemstellingen is besproken. diff --git a/1-Introduction/02-ethics/translations/README.ko.md b/1-Introduction/02-ethics/translations/README.ko.md index e0826564..8f51532a 100644 --- a/1-Introduction/02-ethics/translations/README.ko.md +++ b/1-Introduction/02-ethics/translations/README.ko.md @@ -1,6 +1,6 @@ # 데이터 윤리 소개 -| ![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../sketchnotes/02-Ethics.png) | +| ![ Sketchnote by [(@sketchthedocs)](https://sketchthedocs.dev) ](../../../sketchnotes/02-Ethics.png) | | :-----------------------------------------------------------------------------------------------: | | 데이터 과학 윤리 - _Sketchnote by [@nitya](https://twitter.com/nitya)_ | diff --git a/translations/README.nl.md b/translations/README.nl.md index e5220328..672dc7e8 100644 --- a/translations/README.nl.md +++ b/translations/README.nl.md @@ -19,7 +19,7 @@ Met groot genoegen bieden Azure Cloud Advocates bij Microsoft dit curriculum van **🙏 Speciale dank 🙏 gaat uit naar onze [Microsoft Student Ambassador](https://studentambassadors.microsoft.com/) auteurs, proeflezers en "meedenkers",** notably Aaryan Arora, [Aditya Garg](https://github.com/AdityaGarg00), [Alondra Sanchez](https://www.linkedin.com/in/alondra-sanchez-molina/), [Ankita Singh](https://www.linkedin.com/in/ankitasingh007), [Anupam Mishra](https://www.linkedin.com/in/anupam--mishra/), [Arpita Das](https://www.linkedin.com/in/arpitadas01/), ChhailBihari Dubey, [Dibri Nsofor](https://www.linkedin.com/in/dibrinsofor), [Dishita Bhasin](https://www.linkedin.com/in/dishita-bhasin-7065281bb), [Majd Safi](https://www.linkedin.com/in/majd-s/), [Max Blum](https://www.linkedin.com/in/max-blum-6036a1186/), [Miguel Correa](https://www.linkedin.com/in/miguelmque/), [Mohamma Iftekher (Iftu) Ebne Jalal](https://twitter.com/iftu119), [Nawrin Tabassum](https://www.linkedin.com/in/nawrin-tabassum), [Raymond Wangsa Putra](https://www.linkedin.com/in/raymond-wp/), [Rohit Yadav](https://www.linkedin.com/in/rty2423), Samridhi Sharma, [Sanya Sinha](https://www.linkedin.com/mwlite/in/sanya-sinha-13aab1200), [Sheena Narula](https://www.linkedin.com/in/sheena-narua-n/), Tauqeer Ahmad, Yogendrasingh Pawar -|![ Sketchnote door [(@sketchthedocs)](https://sketchthedocs.dev) ](./sketchnotes/00-Title.png)| +|![ Sketchnote door [(@sketchthedocs)](https://sketchthedocs.dev) ](../sketchnotes/00-Title.png)| |:---:| | Data Science voor Beginners - _Sketchnote door [@nitya](https://twitter.com/nitya)_ |