I’m working on a computer science project and need an explanation to help me understand better.

Competencies

In this project, you will demonstrate your mastery of the following competencies:

• Explain the basic concepts and techniques that pertain to artificial intelligence and intelligent systems
• Analyze current trends and emerging technologies in Computer Science for their impacts on society

Scenario

You are the lead engineer for a major social networking company thatutilizes neural networks in its personalization algorithms.Personalization plays a major role in your business model. The companyis an industry leader in user experience and your customers expect thesoftware to anticipate their needs in terms of recommended posts,recommendations for friends requests, groups to join based on sharedinterests, news articles they may be interested in, discussions they maywant to join, games they may want to play, and other features availableon the site. This experience is monetized through targeted advertising.Your sales reps claim a click-through rate that is double that of yourclosest competitor because you know everything there is to know aboutyour users.

To achieve these results, the company collects user data in the formof mouse clicks, site navigation, links followed, time spent on a page,location data, and so on. Everything a user does within the app isstored and fed into multiple neural networks that create models designedto personalize the user’s experience on the site. In a nutshell, thesealgorithms are designed to create a personalized user experience thatwill maximize the time a user spends on the site and the number of adsthey click on. An EU regulator has brought to the company’s attentionthat you may be violating some aspects of the GDPR law. Specifically,they are concerned that your business model may not conform to some orall of the following principles defined by the law:

1. Transparency: The company must make it clear how they are using data.
2. Purpose limitation: Data may be gathered for pre-specified purposes, not archived and reused for any future use.
3. Data minimization: Only the data gathered for those pre-determined purposes may be gathered, not more.
4. Accuracy: Companies have a responsibility to keep data up-to-date and accurate, and must fix inaccuracies as soon as possible.
5. Storage limitation: Data may only be retained as long as it is applicable to the purposes noted above; it cannot just be stored indefinitely.
6. Confidentiality: Data must be kept secure and confidential to a reasonably expected degree.
7. Accountability: Companies may be held responsible for following these principles and can be penalized if they do not.

You have been asked to write a white paper that addresses theregulator’s concerns. Your white paper will be presented to aninterdepartmental team of systems engineers, software developers, AIexperts, and members of the legal team, so that they can move forwardwith bringing your company into GDPR compliance.

Directions

White Paper

Using your knowledge of how neural networks work and the GDPRprinciples outlined above, write a white paper that addresses theregulator’s concerns. Recommend changes where necessary and defendexisting practices where applicable. Note that proposing remedies to oneprinciple may violate another. In order to adequately address eachaspect of the prompt, you will need to support your ideas with researchfrom your readings. You must include citations for sources that you used.

1. Explain the basics of neural networks and how they work by addressing the following:
   1. Provide a brief explanation of how neural networks work. How do theinput layer, hidden layer, and output layer interact to classifyobjects? Consider the fact that your target audience may have limitedtechnical knowledge.

1. Evaluate how neural networks are used to create personalization by addressing the following:
   1. How are neural networks utilized to aid in the personalization of the user experience?
   2. What ethical concerns can this raise? Consider hidden biases thatmay arise in using a “black box” classification system, where thealgorithms are unknown to the user.

1. Analyze how portions of the GDPR affect personalization by addressing the following:
   1. Summarize the portions of the GDPR that affect personalization. Be sure to consider at least fourof the following in your answer: transparency, purpose limitation, dataminimization, accuracy, storage limitation, confidentiality, andaccountability.

1. Assess how the GDPR is affecting the company’s practices by addressing the following:
   1. What specific legal concerns may arise from your company’s use ofneural networks as a classifier to personalize the user experience?
   2. Is not collecting data a possibility for the company’s business model? Defend your answer.

1. Propose adaptations to the company’s practices to act in compliance with the GDPR by addressing the following:
   1. What are the current trends (best practices) in artificial intelligence and machine learning aimed at preserving privacy?
   2. What changes to the way the company collects, stores, and employsuser data do you propose to comply with GDPR? Defend existing practiceswhere applicable.

What to Submit

To complete this project, you must submit the following:

White Paper
Your submission should be a 3– to5–page Word document with 12-point Times New Roman font, double spacing,and one-inch margins. Sources should be cited according to APA style.

Supporting Materials

The following resource(s) may help support your work on the project:

Website: Guide to the General Data Protection Regulation (GDPR)
Thiswebsite will provide you with a summary of the principles behind theGDPR laws. Begin by reviewing the first page so that you understand thepurpose of the guide. Then be sure to concentrate on each of the pagesunder the “Principles” section. Concentrate on each of the pages underthe “Principles” section as they are outlined in the guide to thegeneral data protection regulation. As you read, be sure to consider howeach principle would impact the company’s business model for yourproject.

Reading: AI and the Janus Face of the GDPR – Chance or Challenge?
Thisreading discusses several impacts of the GDPR on ArtificialIntelligence (AI), including challenges as well as opportunities tocreate a stronger, more reliable AI. As you read, consider the followingquestions:

• What are the potential positive and negative impacts of the standard of transparency for AI?
• What are the potential positive and negative impacts of the standard of data minimization for AI?

Reading: How GDPR Can Undermine Personalization and User Experience
Thisreading discusses some of the challenges that the GDPR creates forbusinesses that use personalization and advertising. It also provides afew suggestions for how businesses can move forward in productive wayswhile still being GDPR-compliant. As you read, consider the followingquestions:

• What principle(s) of the GDPR have affected mailing lists for companies? How are these mailing lists related to personalization?
• What are the benefits and drawbacks of gaining the user’s consent to store cookies when visiting a website?
• What are some of the proposed solutions to help balance thecustomer’s right to privacy and companies’ desire to provide apersonalized user experience?

Reading: How to Develop Artificial Intelligence That Is GDPR-friendly
Thisreading describes the impact of the GDPR on artificial intelligence,specifically the potential impacts on machine learning algorithms. Thereading then suggests some possible methods that can be used to helpprotect user data and enhance compliance with the GDPR. As you read,consider the following questions:

• What is the main conflict between the GDPR and machine learning algorithms?
• What are the specific complications with “black box” algorithms?
• Why is considering potential biases of data sets important? How can biases be addressed?
• What are some of the principles for good data protection?

Reading: Rethinking Data Privacy: The Impact of machine learning
Thisreading provides more detail about data sets and the difficulties inmaintaining privacy for users. It also discusses how machine learningexacerbates these difficulties, as well as describing possible solutionsin more detail. As you read, consider the following questions:

• What is the basic structure of a data set? What are de- andre-identification, and why are they important in thinking about dataprivacy?
• What are some of the specific challenges for AI and machine learning with regard to data privacy?
• What are the emerging trends to preserve privacy? How might they be applicable to the scenario for this project?

Website: General Data Protection Regulation (GDPR) – Official Legal Text
Thiswebsite contains the full text of the GDPR. Some of the other readingsin the Supporting Materials mention specific subsections of the law. Foradditional context about these sections, refer to the relevant sectionsof the GDPR. Note: You are not required to read the entirety of the GDPR official legal text. This website has been included as a reference.