Privacy Risks of Data Collection
Data Collection and Storage can create privacy risks for the users. When a data breach of these storages and collections occur, their data is involved in it. This means that even if a user thinks their data is being kept safe, it might become public information in only a matter of time. Organizations use different methods to protect user data as much as they can. Some of these methods include identifying sensitive data, restricting access, encrypting data, checking for vulnerabilities, informing about cybersecurity practices, and hiring people to protect their network.
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Misuse of Computing Resources
Computer resources are commonly misused when used for criminal purposes. These can include violating policies, misuse of other people’s personal information, phishing, identity theft, hate speech, or copyright infringement. Systems and networks can be protected in a few ways. Some strategies include regularly backing up your data to an external drive, encrypting personal information and files, checking the trustworthiness of downloaded files, and keeping safe from unknown links or downloads.
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Unauthorized Access
Hackers and malicious actors gain access to information in most cases by tricking people. These scams can be shown as links in emails, malware, or hacking through compromised websites/ads. They may also use brute force attacks, exploit known security faults in systems, and simply guess through weak security. Some methods or cybersecurity measures used to prevent data breaches are using strong passwords, multi-factor authentication, having security audits, preventing physical access to networks, and using data loss prevention software.
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Benefits and Risks of Computing Innovations
Computing innovations can create cybersecurity risks or other impacts in many ways. First off, they can create similar risks to those mentioned before. These being data monitoring, data breaches, or also lack of user control. They can also create other physical risks, such as system failures, social isolation, excessive energy usage, excessive e-waste creation, resource depletion, and even global supply chain disruptions. One majorly relevant instance where technological advancements had unintended consequences is generative AI. It came with two of the before mentioned common consequences, being excessive energy consumption and data leakage. Because of generative AI’s high need for energy, it also needs a high amount of creation of energy. This energy can sometimes be created in ways which harm the environment. Also, when AI is given information, it could create a vulnerability for data to be mishandled or given out. AI also has another major consequence, being that it may damage people’s higher level reasoning skills. When worker’s tasks are outsourced to AIs, it will improve the AIs decision making skills, however can damage a person’s.
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