From f1d8a8816b53c3d1bf03a43ae52dd42bf9a2887f Mon Sep 17 00:00:00 2001
From: Jen Mankoff <jmankoff@cs.washington.edu>
Date: Mon, 28 Oct 2024 10:19:59 -0700
Subject: [PATCH] fixed week
---
assignments/technology-implementation.md | 2 +-
slides/bias-in-machine-learning.html | 18 +++++++++---------
2 files changed, 10 insertions(+), 10 deletions(-)
diff --git a/assignments/technology-implementation.md b/assignments/technology-implementation.md
index f9839239..fe8ba6c7 100644
--- a/assignments/technology-implementation.md
+++ b/assignments/technology-implementation.md
@@ -35,7 +35,7 @@ To complete this assignment, please do the following:
You should identify a technology you have implemented *for general use* (i.e. not an accessibility technology). Ideally this should be an interactive technology (some kind of user interface, app, etc). If you have no such thing, you can ask to approve using a website or other static content that you have generated as an alternative.
{% details Possible examples (this list is still under construction) %}
-- A class assignment that has an interface (web, mobile or other). If you've built a mobile app for 340, built a website for 154, or taken 331 (such as the campus map website) these are all things you could use.
+- A class assignment that has an interface (web, mobile or other). If you've built a mobile app for 340, built a website for 154, or taken 331 (such as the campus map website) or 442 (if you made a website) these are all things you could use.
- A web or mobile app you built yourself
- A profile of yourself on linked in, tiktok, or any other site where you've posted content.
- Your personal website (even if it's hosted somewhere else like wordpress)
diff --git a/slides/bias-in-machine-learning.html b/slides/bias-in-machine-learning.html
index 69e6c546..0645c8ed 100644
--- a/slides/bias-in-machine-learning.html
+++ b/slides/bias-in-machine-learning.html
@@ -1,13 +1,13 @@
---
layout: presentation
-title: AI Accessibility Bias --Week 7--
+title: AI Accessibility Bias --Week 6--
description: Discussion of Bias in AI
class: middle, center, inverse
---
background-image: url(img/people.png)
.left-column50[
-# Week 7: Automating Accessibility
+# Week 6: Automating Accessibility
{{site.classnum}}, {{site.quarter}}
]
@@ -166,6 +166,12 @@ as disabled <q>based on a hunch</q>.
- Make predictions
+---
+---
+# QUICK BREAK
+
+Good time to stand and stretch
+
---
# How do we Evaluate Predictors/Predictions?
@@ -205,6 +211,7 @@ Examples:
- **Make predictions**
+
---
# Example: Resume study (1/2)
@@ -245,7 +252,6 @@ Awards and honors
- Tried this with 6 “Disability†CVs [Disability, Blind, Deaf, Autism, Cerebral Palsy, Depression] vs. a CV Missing Disability Items
- Gave ChatGPT 10 tries per CV
----
---
# What should have happened
@@ -256,12 +262,6 @@ Bar chart titled: “What should have happenedâ€. The X axis shows number of ti
What should have happened is that the CVs with the awards (the disability items), which are all prestigious, wereranked first 10 out of 10 times.
----
----
-# QUICK BREAK
-
-Good time to stand and stretch
-
---
# What happened
--
GitLab