Privacy in AI-Driven Systems and Challenges

in Cent7 months ago

Greetings to my esteemed friends on the Cent platform and the entire Hive blockchain. It's another day to share my thoughts on privacy in an AI-Driven systems and give my recommendations on how this can be achieved. It's your friend @faquan, saying hello from this part of the world.

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One of the major challenge facing the Internet as a whole is the privacy of users contents, information and wallets. In a growing world of hackers and the fight to protect users from cyber security challenges and the rise of AI users, the question is, can the data of AI users be safe and secured in an AI-Driven systems?

I think that the reason why Web 3 technology was created was to give users the opportunity to singlehandedly operate their wallets and as well have privacy of content. Although the Web 3 technology goes beyond just privacy and encompasses many other benefits.

Challenges facing AI-Driven Systems

  • Technical Difficulties:
    Some of the most common technical AI challenges organizations must overcome when implementing AI include storage, security, and scalability. Since the volume of data related to AI is very high, companies must invest in strong infrastructure capable of handling its complexity. User trust relies on building data security and ensuring privacy throughout the AI lifecycle.
    It should be noted that once privacy is removed from the AI-Driven systems, then the aims of the system is defeated. To this, AI systems should be well secured from external and internal interference in order not to breach the users trust.
  • Security Risks:
    Malicious actors can exploit AI systems and perform complex cyberattacks, bypassing security measures and exploiting system vulnerabilities. It's a well known issues both in the blockchain technology and other internet airspaces.

  • Bias and Discrimination:
    Developers of AI applications can continue the ongoing bias that have been suffered in the past. This is because AI applications and data installation are done by humans who might have this ongoing bias. This prevents fairness and inclusivity in AI applications.

In conclusion, privacy in AI-Driven systems is one that's so important and will give confidence to AI users. As the growth and development of the AI technology continues, developers must make it a point of duty to preserve and secure users data and information and be void of bias and improve on the level of security to prevent cyber attacks.

What do you think about privacy in AI-Driven systems? Is it possible to achieve that. Please drop your views at the comment section.

Thank you

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