clean/03_ethics.ipynb

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   "source": [
    "#hide\n",
    "! [ -e /content ] && pip install -Uqq fastbook\n",
    "import fastbook\n",
    "fastbook.setup_book()"
   ]
  },
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   "source": [
    "# Data Ethics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sidebar: Acknowledgement: Dr. Rachel Thomas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### End sidebar"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Key Examples for Data Ethics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bugs and Recourse: Buggy Algorithm Used for Healthcare Benefits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feedback Loops: YouTube's Recommendation System"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bias: Professor Latanya Sweeney \"Arrested\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Why Does This Matter?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Integrating Machine Learning with Product Design"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Topics in Data Ethics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Recourse and Accountability"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feedback Loops"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Historical bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Measurement bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Aggregation bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Representation bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Addressing different types of bias"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Disinformation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Identifying and Addressing Ethical Issues"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analyze a Project You Are Working On"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Processes to Implement"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Ethical lenses"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Power of Diversity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fairness, Accountability, and Transparency"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Role of Policy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Effectiveness of Regulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Rights and Policy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Cars: A Historical Precedent"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Questionnaire"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Does ethics provide a list of \"right answers\"?\n",
    "1. How can working with people of different backgrounds help when considering ethical questions?\n",
    "1. What was the role of IBM in Nazi Germany? Why did the company participate as it did? Why did the workers participate?\n",
    "1. What was the role of the first person jailed in the Volkswagen diesel scandal?\n",
    "1. What was the problem with a database of suspected gang members maintained by California law enforcement officials?\n",
    "1. Why did YouTube's recommendation algorithm recommend videos of partially clothed children to pedophiles, even though no employee at Google had programmed this feature?\n",
    "1. What are the problems with the centrality of metrics?\n",
    "1. Why did Meetup.com not include gender in its recommendation system for tech meetups?\n",
    "1. What are the six types of bias in machine learning, according to Suresh and Guttag?\n",
    "1. Give two examples of historical race bias in the US.\n",
    "1. Where are most images in ImageNet from?\n",
    "1. In the paper [\"Does Machine Learning Automate Moral Hazard and Error\"](https://scholar.harvard.edu/files/sendhil/files/aer.p20171084.pdf) why is sinusitis found to be predictive of a stroke?\n",
    "1. What is representation bias?\n",
    "1. How are machines and people different, in terms of their use for making decisions?\n",
    "1. Is disinformation the same as \"fake news\"?\n",
    "1. Why is disinformation through auto-generated text a particularly significant issue?\n",
    "1. What are the five ethical lenses described by the Markkula Center?\n",
    "1. Where is policy an appropriate tool for addressing data ethics issues?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Further Research:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Read the article \"What Happens When an Algorithm Cuts Your Healthcare\". How could problems like this be avoided in the future?\n",
    "1. Research to find out more about YouTube's recommendation system and its societal impacts. Do you think recommendation systems must always have feedback loops with negative results? What approaches could Google take to avoid them? What about the government?\n",
    "1. Read the paper [\"Discrimination in Online Ad Delivery\"](https://arxiv.org/abs/1301.6822). Do you think Google should be considered responsible for what happened to Dr. Sweeney? What would be an appropriate response?\n",
    "1. How can a cross-disciplinary team help avoid negative consequences?\n",
    "1. Read the paper \"Does Machine Learning Automate Moral Hazard and Error\". What actions do you think should be taken to deal with the issues identified in this paper?\n",
    "1. Read the article \"How Will We Prevent AI-Based Forgery?\" Do you think Etzioni's proposed approach could work? Why?\n",
    "1. Complete the section \"Analyze a Project You Are Working On\" in this chapter.\n",
    "1. Consider whether your team could be more diverse. If so, what approaches might help?"
   ]
  },
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   "metadata": {},
   "source": [
    "## Deep Learning in Practice: That's a Wrap!"
   ]
  },
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   "source": [
    "Congratulations! You've made it to the end of the first section of the book. In this section we've tried to show you what deep learning can do, and how you can use it to create real applications and products. At this point, you will get a lot more out of the book if you spend some time trying out what you've learned. Perhaps you have already been doing this as you go along—in which case, great! If not, that's no problem either... Now is a great time to start experimenting yourself.\n",
    "\n",
    "If you haven't been to the [book's website](https://book.fast.ai) yet, head over there now. It's really important that you get yourself set up to run the notebooks. Becoming an effective deep learning practitioner is all about practice, so you need to be training models. So, please go get the notebooks running now if you haven't already! And also have a look on the website for any important updates or notices; deep learning changes fast, and we can't change the words that are printed in this book, so the website is where you need to look to ensure you have the most up-to-date information.\n",
    "\n",
    "Make sure that you have completed the following steps:\n",
    "\n",
    "- Connect to one of the GPU Jupyter servers recommended on the book's website.\n",
    "- Run the first notebook yourself.\n",
    "- Upload an image that you find in the first notebook; then try a few different images of different kinds to see what happens.\n",
    "- Run the second notebook, collecting your own dataset based on image search queries that you come up with.\n",
    "- Think about how you can use deep learning to help you with your own projects, including what kinds of data you could use, what kinds of problems may come up, and how you might be able to mitigate these issues in practice.\n",
    "\n",
    "In the next section of the book you will learn about how and why deep learning works, instead of just seeing how you can use it in practice. Understanding the how and why is important for both practitioners and researchers, because in this fairly new field nearly every project requires some level of customization and debugging. The better you understand the foundations of deep learning, the better your models will be. These foundations are less important for executives, product managers, and so forth (although still useful, so feel free to keep reading!), but they are critical for anybody who is actually training and deploying models themselves."
   ]
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