The ethical, political, and ideological issues surrounding AI/ML applications (is that real or exaggerated?)

Although Artificial Intelligence (AI) and its subfields like Machine Learning (ML) and Deep Learning (DL) have very various good uses, they were used in a bad way to surveil and target colored and minority communities (Solon, 2019).

AI facial recognition systems were used to track possible violent people. Unfortunately, the bad training dataset made some of those systems detect dark-skinned people as a potential threat (Hao, StopAIethics-washing-and-actually-do-something, 2019) (Hao, 2018).

Some experts expressed their concerns about the future effects of AI technologies. Two important issues of ethical, political, and ideological issues surrounding AI/ML applications are data abuse and the deep fake (ANDERSON & RAINIE, 2018).

Data Abuse

Facebook and Twitter gather massive information from users and use them to suggest recommendations based on the user’s interests. Facebook AD preference, for example, uses data such as political leaning and racial/ethnic affinities to generate materials for them. 60% of users assigned a multicultural affinity class said they have a very strong affinity for their assigned group. Most social medial users believe that these platforms can detect their main features like race, political opinion, religious beliefs, etc. However, there are variations between what platforms say about users’ political ideologies and what users are (Hitlin & Rainie, 2019).

Some advertisers use multicultural affinity AI tools to exclude certain groups of races through work interviews. Some studies say that AI is responsible for these problems. We can say that not AI in specific, but the wrong use of AI application causes those problems.

Variations of the training database affect the performance of AI systems. In a study of gender identification based on deep learning (WOJCIK & REMY, 2019), DL algorithms failed to detect dark-skinned people. In fact, the size of their database was very low. The study also did not take into account all possible races and ages. Therefore, the results of this study cannot be considered as accurate results.

Flickr website images used by IBM Company to train their face recognition. The problem is that you don’t know if your images were used by IBM or not, but the fact is that IBM can use your photos because you used Creative Common License, allowing nonprofits to use your photos for free!. Some people were annoyed about using their photos, while others said they could enhance the face recognition systems. In some countries, if IBM did not respond to your request for removing photos, you can complain to your data protection authority systems (Solon, 2019).

Deep Fake

The “” website was developed by Philip Wang to generate an infinite number of fake images. His technique was based on AI and used a very large dataset of real images. StyleGAN networks that were used in this website can accept not only humans’ faces but also any source helping graphical and animation designers to develop their applications (Games, Films Tricks, etc.). However, this technique can create fake videos by pasting people’s faces on target videos (Vincent, 2019). Trump appeared in a video offering advice to people of Belgium in case of climate change which was a fake film constructed by these deep fake networks. Some kind of bad use of AI can cause political criticisms and even mayhem (Schwartz, 2018). Maybe traditional Photoshop fake images would have the same bad effects by this AI technology.

Optimistic Future

Although all previous bad usage of AI, new detection methods have arisen. Fortunately, large groups of AI researchers are aware of AI ethics and have taken many approaches to solve this problem, like developing algorithms to reduce hidden biases within training datasets. They also focus on applying a process that holds AI companies responsible for fairer results (Hao, This_is_howAI_ bias_really_happens, 2019). Facebook committed to developing an ML algorithm detecting deep fakes (Schwartz, 2018). Some other AI researchers developed approaches to detect and reduce hidden biases within datasets (Hao, This_is_howAI_ bias_really_happens, 2019), (Hao, StopAIethics-washing-and-actually-do-something, 2019). AI companies protect user privacy, combating deep fake and taking into account wider datasets.

AI is the digital future of the world. Its benefits are obvious in all fields (Medical diagnosis, Data mining, Robotics, Big data analysis, image recognition, military application, security application, etc.). Deep fake also has positive benefits, like creating digital voices for people who lose theirs to diseases (Baker & Capestany, 2018).

Many high-profile initiatives established in the interest of socially beneficial AI and highly reputable. Like Montreal and IEEE, some principles said that the development of AI should ultimately promote the well-being of all humans. Other principles focused on the common good or benefit of AI applications’ humanity (Floridi & Cowls, 2019).


Baker, H & Capestany. C2018). It’s Getting Harder to Spot a Deep Fake Video. Retrieved from:

Vincent, J. (2019). uses AI to generate endless fake faces. Retrieved from:

Anderson, J. & Raini, L. (2018). artificial-intelligence-and-the-future-of-humans. Retrieved from:

Hao, K.. (2018). Retrieved from:

Hao, K. (2019). StopAIethics-washing-and-actually-do-something. Retrieved from:

Hao, K. (2019). This_is_howAI_ bias_really_happens. Retrieved from:

Floridi, L. & Cowls, J.. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review.

Solon, O.. (2019). facial recognition, dirty little secret. Retrieved from:

Schwartz, O.. (2018). deep-fakes-fake-news-truth. Retrieved from:

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Wojic, S. & Remy, R. (2019). The challenges of using machine learning to identify gender in images. Retrieved from:

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About Heba Khashogji

As a true believer in the seeds of obedience that blossom in our lives my life found happiness in honoring my parents. This leads me to the passion I’ve been fulfilling, to be an agent of change both in the corporate and societal environment. I advocate to work on social services to create and promote equity, opportunity and improvement of the people and the community. I offer more than a decade of experience and accomplishment in human resource, driving implementation in employee development, quality management systems, salary standardization, compensation and benefits management, personnel services management and company reorganization and realignment. One of my achievements is the creation of a quality management procedures and policies as an strategic and tactical efforts that drove our company, Khashoggi Holding Company in its International recognition as Quality Crown Gold Awardee in 2014. Going back, when I started working as a volunteer accountant/admin to setup Dar AlHekma College, the first private college for ladies in the Saudi Arabia and my first official career in King Fahad Armed Forces Hospital, I developed an interest in human relations and developed this interest into my participation to the implementation of quality management and standardization of policy management systems in these organizations. Demonstrating initiative in the start, I applied and implemented integration programs in Personnel Section leading to employees' satisfaction by delivering fair and reasonable benefits to all. Throughout my career, I had the opportunity to establish a strong network contacts in and out of the country through my active participation in several seminars and workshops. The scope of my experience has spanned practically in all aspects of HR as well as leadership. Another passion I am in love with is the aiding to the propagation of young Saudi generation be with better traits and characters created children books, converted to animated videos shown in local TV channels to help reinforcing behavioral change in the Arab region bringing them to be more well-mannered individuals and be more diplomatic among them as well as with their foreign friends exercising tact and courtesy in every encounter. Just recently, another 2 things in my wish list are achieved, to skydive and take Master course. Skydiving made me challenge myself and conquer my fears that can help me overcome obstacles in my future. I am not stopping to dream and I am not stopping to learn. I still see myself in a class, for 23 years from now, physical or virtual. I thirst for knowledge and I always crave for new ideas not even in the time of pandemic.