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Irritants of Artificial Intelligence and Data Protection

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As the impact of Artificial Intelligence in everyday life substantial, there’s a need that AI applications don’t undermine the right to data protection. Read on to know more…

As the impact of Artificial Intelligence (AI) and Machine Learning (ML) in everyday life substantial, there’s a need that AI applications don’t undermine the right to data protection. When the the entire globe converges into a digital community, the advancement and implementation of AI is well on its way to making considerable strides in increasing productivity and reliability in global market places and economies. But again, as with any great progress, there are challenges of sensitive information being compromised.

Necessity
Data is necessary not only for Artificial Intelligence to achieve its full potential and to prevent monopolization of critical AI, but also to guard against bias or error. If we don’t have the underlying data, it is far more difficult to detect or remediate discriminatory outcomes. Moreover, large, enterprise data sets are essential for Artificial Intelligence to serve underserved segments of the population.

Artificial Intelligence’s need for personal, even sensitive data is widely recognized. Most applications of AI and ML require huge volumes of data in order to learn and make intelligent decisions. In fact, rather than sample data, AI often works by collecting and analyzing all of the data that is available.

AI & Data Protection
Most AI tools use substantial amounts of data. With few exceptions, more data is better than less, and there is almost never enough. In recent months, a great deal of ink has been spilled on AI and data protection. Throughout the inception stages of AI, predominantly from 2015, it has become vital that AI applications should pay attention to mitigating the probable risks of processing personal data.

Ensuring that proper data protection procedures are in place when dealing with AI, would mean less vulnerability, especially when dealing with data subjects and the control rights over that data. All these concerns will have to be considered carefully taking into account the provisions of EU Regulation 2016/679, General Data Protection Regulation (GDPR).

Challenges
The enhancement of AI systems entails a material issue with reference to the purposes of the data processing. This issue is directly connected with the ML features of an AI system – i.e., the ability of an AI system to interact with the surrounding environment, to learn from the experience, and to address future behaviors based on such interactions and learnings. AI and ML features may cause the processing of personal data to be carried out in various ways and for different purposes than those for which it was originally set. This may result in the complete loss of control, by the data subjects, of their data. Any such loss of control is obviously against the principles of GDPR.

On the legal aspects of data protection, it is often a challenge to identify the legal basis for the personal data processing, in addition to the general legal basis of the performance of a contract between the data controller and the data subject. Legitimate interest may also be critical, as it requires a difficult balance between the rights of the data subjects and the legitimate interests of the data controller; there are no clear guidelines on how to carry out such balance. Setting up the legal basis and purposes of the personal data processing remains one of the most important features to take into account when dealing with AI systems and related ML features.

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