Artificial intelligence (AI) technology has been advancing at an unprecedented rate in recent years. With the advent of machine learning algorithms and big data analysis, AI has made significant strides in several fields, including healthcare, finance, transportation, and retail. However, Data Privacy is one of the most significant challenges of AI technology and is making headlines with the exponential growth of ChatGBT.
Data Privacy is the right of an individual to control their personal information, which includes the collection, use, storage, and sharing of data. In the context of AI, data privacy is a critical concern because machine learning algorithms require vast amounts of data to learn and improve their accuracy. Therefore, Data Privacy violations could have significant consequences for individuals, including identity theft, financial fraud, and reputational damage. An in-depth Privacy assessment is recommended before introducing such technology.
Challenges for Businesses Using AI
One of the significant challenges of Data Privacy with AI technology is the issue of data security. Hackers and cybercriminals can exploit vulnerabilities in AI systems to gain access to sensitive information, such as credit card numbers, social security numbers, and medical records. Therefore, AI systems must have robust security measures to protect against data breaches and other cyber threats. Failure to have these measures in place could lead to high levels of penalties from various data protection regulators around the world where business customers reside.
Risk of Bias and Discrimination
Another challenge of data privacy with AI technology is the issue of bias. Machine learning algorithms learn from the data they are trained on, and if the data is biased or incomplete, the algorithm will produce biased results. For example, if an AI system is trained on biased data against a particular race or gender, the system will produce discriminatory results. Therefore, ensuring that the data used to train AI systems is diverse, inclusive, and unbiased is crucial. This can be challenged in Data Subject Access Requests.
What about Data Protection Impact Assessments
Privacy concerns with AI technology are not limited to collecting and using personal information. Another challenge is the issue of explain ability. AI algorithms are often opaque and difficult to interpret, which makes it challenging to understand how they arrive at their conclusions. This lack of transparency could undermine public trust in AI systems and make it easier to hold organisations accountable for their actions. For Data Controllers, if AI is used in automatic decision-making, how do you explain transparently how such decisions are made and how they can complete balanced Data Protection Impact Assessments? DPIA
AI and Consent
Finally, the issue of consent is also a significant challenge with data privacy in AI. In many cases, individuals may not be aware that their data is being collected or need help understanding how it will be used. Therefore, it is crucial to obtain informed consent from individuals before collecting their data and to provide them with clear information on how their data will be used and protected.
In conclusion, Data Privacy is one of the most significant challenges facing AI technology today. As AI continues to evolve and become more pervasive, it is crucial to address these challenges to ensure that individuals’ privacy rights are protected. To achieve this, organisations must implement robust security measures, ensure that data used to train AI systems is diverse and unbiased, make AI algorithms more transparent and interpretable, and obtain informed consent from individuals before collecting and processing their data.
Formiti Data International are renowned in complex industries to deliver Data Privacy Compliance, including assessing AI technologies processing individual’s Personal Data. Now launching their Formiti101 Privacy Management Platform