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AI & ML - Coggle Diagram
AI & ML
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Cybersecurity Advantages
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Ethical Issues
Scenario 1 : An AI system analyzes email traffic and flags phishing attempts, preventing employees from falling victims to scams
Unethical : Allow the AI system to continue monitoring without protections for employees in cases of privacy
Ethical (My Choice) : Ensure email monitoring is being done ethically and only for security purposes with clear boundaries
Scenario Two : An Ai-driven firewall automatically blocks suspicious IP addresses that attempt unauthorized access to a network
Ethical (My choice) : Provide manual override options and ensure proper access to authorized individuals
Unethical : It is necessary for AI to have the ability to block any IP address it sees as a potential threat
Ethical Theory Used for Justification : Social Virtues, the forces that drive us to act and think certain ways "do the right things, for the right reasons, in the right kinds of situations"
Threat Detection
References the ability for AI systems to identify suspicious activities or unusual beahvior that could indicate a security threat. Examples include hacking, phishing, and malware
Cybersecurity Risks
AI Powered Cyberattacks
References deliberate actions where attackers use AI algorithms to enhance cybercrimes. Examples include elaborate phishing schemes, password cracking, and malware able to evade detection
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Ethical Issues
Scenario 1 : Hackers use AI to automate the creation of phishing emails that are highly personliazed, making them hard to detect
Ethical (My Choice) : Help prevent the use of AI in schemes like this through cybersecurity law and regulation
Nonethical : Allow the AI to continue the scheme of phishing and potentially falll victim or allow others to fall victim to the attack
Scenario 2 : Hackers give incorrect data to a self driving car's Ai system, which cause the vehicle to make the wrong decisions
Ethical (My Choice) :Strengthen AI security systems to ensure that hackers aren't able to easily access a self driving car. In addition to user override to prevent accidents or poor decision making
Nonethical : Do not solve the issue and cause potential accidents and harm to occur to others. Eventually leading to lawsuits and the loss of company reputation
Ethical Theory Used for Justification : Utilitarianism and the principle of utility, "Everything we do and everything in society should strive to maximize pleasure and minimize pain"
Ethical Challenges
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Bias and Discrimination
Refers to the biases contained in the data that AI systems are trained on can cause them to be imbalanced. The may have discriminatory effects, such as racial profiling or unfair hiring procedures
Ethical Issues
Scenario 1 : A softeware company uses AI in the hiring process to screen resumes and assess candidates based on past hiring data
Ethical (My Choice) : Ensure that the data and development of the AI system used in the hiring process is free from bias and that the program is transparent in it's selection process
Unethical : Allow the AI system to continue assisting the company in the hiring process, without ensuring that ethical standards are being met and potential biases and discrimination are being handled
Scenario 2 : A social media company is failing to curtail fake news and information from its platform. Allowing manipulative information and deep fakes to exist without challenges
Ethical (My Choice) : Attempt to establish an ethical framework to stop the spread of fake news and misinformation to ensure the platform maintains it's integrity and safe space for users
Unethical : Let misinformation and fake news continue to spread throughout the platform, despite it's potential ethical and societal issues
Ethical Theory Used for Justification : Kantian Ethics, ethical principle "... we should so act that we always treat the humanity in each person - in our own person as well as in other people - as an end in itself, and never merely as a means"