Nadim Khammar | Digital Director – CNN Middle East


1. Why is the rise of artificial intelligence technology so important in the media and entertainment industry?


The global business community is unanimous in its perception that AI is slowly but surely changing the world. It’s projected gains across productivity, efficiency, automation and costs will enable consumers and businesses to truly capitalize on the promise of the digital economy.

The rise of A.I technology and its applications can be seen right across the global economy, and perhaps most visibly across the entertainment and media sector itself.

AI software has already transformed the industry, a direct influence that has altered consumer’s everyday experience in this new age of media consumption. AI’s technology suite is playing a transformational role that’s unfolded within a generation across our everyday lives. What broadly started as exploring ways to effectively automate processes and reducing human work scope, has given rise to A.I’s pivotal role across the media value chain, with its suite of solutions now managing the most critical components of the business today. Film & TV production, streaming platforms, social media, digital advertising are but a few of the business functions that are powered by A.I solutions.

With ever-growing efficiency levels across accuracy and scale, down to the very nature of the technology’s architecture, A.I intelligence is ushering in innovation across the global media and entertainment industry. As we look ahead and wonder what the evolution of media and entertainment will be, it is without a doubt tied to the development of A.I within the industry and unpredictable


2. Does AI fundamentally change how the media / entertainment industry serves the economy?


There is no doubt the profound effect A.I will have on global business, as consulting firm Price Waterhouse Cooper estimates that by 2030 A.I will potentially contribute $15.7 trillion to the worldwide economy. Yet we are still very much in the early stages of A.I development, with industries laying the foundations for successful change. This is coming across in the form of investments, training, yet also the development of cultural acceptance due to the disruption A.I will introduce to the workplace.

Mainstream media’s focus has been on the effects A.I solutions has had on the titans of the entertainment industry – such as big tech to film studios. There is certainly wider scale adoption taking place across the industry, with disruption to the wider business of creative arts an eventuality. The scale of those effects will come down to the creation of software that provides the workforce with the ability to harness the technology.

With the rise of open-source software tools and low-cost computational platforms, we are witnessing how this is virtually taking place across all disciplines of content creation, production, and its distribution.

If we explore news gathering and journalism, we are starting to see A.I-powered solutions that can truly augment the industry. Machine learning can generate original content, all within the boundaries of institutional oversight. The long-term effects could enable journalists to not only break news quicker but more importantly give them back the time to focus on deeper analysis. It’s now a question of how and when the technology will be embraced, especially by smaller outlets in dire need of support, as disruption brought on by tech platforms are driving them out of business.

The advantages of AI adoption will no doubt lead to the reskilling of the workforce across many industries. The natural worry has been that AI will reduce job opportunities, while in fact it should be embraced for it’s potential to enhance their abilities beyond human limitations and drive innovation in their field. Across all aspects of the entertainment and media business, there will continue to be profound disruption to their business models that will have a significant impact on how the industry serves the global economy.


3. Are current media practices adequate for overseeing an AI-driven industry?


Far from it. The industry naturally face the same challenges as all others, across effective data engineering, securing legislation across data governance, data privacy.. we are only starting to see the foundations laid for generations to come.

The hurdles presented by AI and ML algorithms in the way people are exposed to content and get their information remains a hot topic.

Misinformation and bias issues have come to the forefront, with tech platforms taking the brunt of the blame for not safeguarding its audiences from the content posted on its platforms. The 2016 U.S elections is a prime example of such an instance, calling into question the role of the platforms in enforcing stricter regulation to ensure the accuracy of content on its sites.

Governments and the private sector have taken notice and taken action on some fronts, such as data privacy. We have seen legislation introduced over the past several years to protect data privacy to better regulate how businesses all over the world are allowed to handle personal information – the Global Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) are prime examples. That said we certainly need a lot more done in this area; it requires both the government and private sector to compromise and align effectively in the best interest of consumers.


4.What are the main uses for AI in the media and entertainment industry? Where do you see AI technology headed in your field?


The application of AI solutions across the industry is broad and varies across sectors. A few examples:

  • Film & TV – recommendation engines, personalized targeting, search optimization and content automation all factor heavily in the early successes of streaming platforms and film studios.

  • Music – similar to the technology adopted by streaming platforms, the segmentation builds across music platforms like Spotify and Anghami are powered by machine learning algorithms.

  • Gaming VR/AR – AI plays a key role in the advancement of virtual and augmented reality in gaming technology and simulation training.

  • Journalism – AI that generates text is widespread in journalism and used by publishers to expand the range of offerings.

  • Advertising – personalized data that feeds into programmatic technology to serve consumers the most relevant and appropriate advertising. An example of such a proprietary solution is CNN’s Sentiment Analysis Moderator (S.A.M) tool built for advertisers to unlock the full potential of news environments.

The news category is unique and requires a more sophisticated approach than legacy brand safety and content classification tools on offer. To meet these unique needs, CNN technology was developed with a focus on truly understanding the nuances of both context and sentiment and applying those insights across all CNN news content.

Through a combination of data, A.I technology along with human-centered design, we are building towards an interconnected media experience that is fully immersive and personalized.

In that sense AI’s adoption across the sub sectors will continue to evolve and draw parallels as they strive to deliver and match consumer expectations.