Hassan Taher’s roots as a technologist and a futurist date back to his childhood in Beaumont, Texas. As the son of an engineer and a math teacher, he was steeped in science education as a child. And Taher also gravitated toward science fiction at a very early age, developing a deep love and appreciation for the work of masters such as Isaac Asimov and Arthur C. Clarke.
Although Asimov and Clarke regularly demonstrated the tremendous potential of AI in their novels, they certainly didn’t shy away from its many hidden dangers and unintended consequences. In other words, they were ideal models for a young man who would one day grow into a respected thought leader in the world of artificial intelligence (AI).
While studying computer science at the University of Texas, he was an active member of the campus Artificial Intelligence Club. He continued to investigate the vast potential of AI after graduation, writing widely on the topic and ultimately founding the successful business consultancy Taher AI Solutions.
Taher AI Solutions advises and guides a broad variety of organizations who want to leverage the power of AI technology in their operations. Under Taher’s leadership, it serves clients in sectors that range from healthcare to finance to manufacturing. Over the years, Taher AI Solutions has garnered a reputation for using AI in a strategic and principled manner.
As the head of Taher AI Solutions, Hassan Taher has played in integral role in the development and integration of AI that is designed to maximize benefit while minimizing risk. With cybersecurity threats lurking everywhere, data privacy issues are a paramount concern for Taher and other AI experts around the world. While AI comes with a specific set of data privacy vulnerabilities, tech leaders can protect their businesses and customers through appropriate safety standards and responsible practices.
“AI systems, especially large language models, require vast amounts of data for training, much of which comes from the internet” explains Hassan Taher. “This has raised concerns among individuals, publishers, and privacy advocates about how their personal data is being used without explicit consent.” Taher sites the use of personal data by organizations such as OpenAI, Google, and Meta as examples of this growing problem and public pushback against it.
The AI systems of OpenAI, Google, Meta, and other major tech players require massive datasets for training purposes. These systems rely upon these datasets to learn to recognize valuable patterns and provide intelligent, human-like responses. Problems can arise, however, when companies fail to source sensitive information in an unethical manner.
“Much of the data used in training is scraped from the web without clear permissions from users or content creators,” writes Hassan Taher. “For many, this raises ethical questions about whether these AI models respect the privacy rights of individuals and businesses whose data is being exploited.”
As AI scrapes the internet for content, clever content creators are learning how to protect their work from potential unauthorized use. “One approach involves adding specific code to websites that blocks AI crawlers from accessing certain material,” Taher explains. “This has become a popular method among those looking to safeguard their intellectual property from AI training bots like Google Bard and OpenAI’s ChatGPT. For example, web developers can implement technical barriers such as the ‘robots.txt’ file, which tells web crawlers what content is off-limits.”
Beyond limiting access to online content and information, tech and legal experts are deeply concerned about exactly who profits from the highly valuable data and intellectual property in the AI ecosystem. Publishers argue that while AI companies benefit from the insights gained through data scraping, the content creators who produce this data are often left out of the conversation and the rewards,” Hassan Taher reports.
Managing the complex mechanics of data mining is an extraordinary challenge for large corporations and federal institutions. So it should come as no surprise that the average person faces a steep uphill climb when it comes to protecting their sensitive information and addressing their online privacy concerns. “For individual users, the question of how their personal data is being used in AI training is increasingly difficult to navigate,” writes Taher. “Many users are unaware that their digital activities, from social media posts to online reviews, can be utilized by AI models to improve machine learning algorithms. A lack of transparency in data usage has prompted privacy advocates to demand clearer regulations and user rights over their online footprint.”
Fortunately, this public outcry has led to considerable action by elected officials and government bodies at both the national and international levels. This action has led to passage of important data privacy legislation that offers data privacy protection that specifically addresses AI learning. “Data privacy laws, such as the General Data Protection Regulation (GDPR) in Europe, have created some safeguards by giving individuals the right to control their personal information,” Hassan Taher points out. “Under GDPR, AI companies must seek consent from users before collecting and processing their data for model training purposes. However, these regulations are often limited to specific regions and have yet to be universally adopted.”
So the path forward for data privacy in the world of AI will be rocky to say the least. But with the right momentum and approach, Hassan Taher believes that data mining can support AI learning in a highly transparent and ethical way. After all, individuals and organizations around the world are standing strong against the use of private data and intellectual property without consent. And this rapidly growing movement isn’t likely to go away anytime soon.
“For now, the onus is on both AI developers and those affected by data scraping to find a middle ground that respects privacy while enabling innovation” Taher concludes. “While AI has the potential to drive significant advancements, it is clear that without clear consent mechanisms and legal safeguards, the tension between data privacy and AI development will remain a contentious issue.”
