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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.

5. How can the media industry be better prepared to tackle business in the next five years?

The one constant is change: the digital disruption ushered in the recalibration of business models across the industry. As we look forward to the next 5 years, what will the next wave of advanced technology – 5G, internet of things comes to mind – mean for the industry and for the development of A.I technology?

Embracing A.I technology leads that agenda. As consumers shift to a truly interconnected media experience, no media business will exist in 5 years that has not truly adopted A.I technology solutions.

As the audience demand for a premium personalization model at scale - not about curating one experience, but for tens of millions – businesses will need to reconsider their role and identity within that experience and if they are truly built for the future. And through that self-discovery, businesses can and will discover dynamic opportunities that could see them transform their business across sectors.


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If I were to be asked which sector is AI disrupting the most today with immeasurable prospects, my answer would be with a heart beat: Healthcare.

The healthcare sector is one of the most diversified fields today, therefore the applications of AI is continuously tested and retested to make use of all the value can be extracted from artificial intelligence in favor of the patient and the sector as whole.

In my practice I have witnessed the shift of many of our daily activities from patient care to recording to diagnostics all of which have been of great value for us as practitioners.

Artificial Intelligence accuracy is unequalled. the level of accuracy of machines is something that we cannot overlook and is getting better by the day.

I see in the near future AI will have a greater penetration and acceptance, yes there is still resistance from healthcare practitioners but this is fading as the value is undeniable!

Many questions are paused when a the topic of AI in healthcare is raised from my fellow practitioners some of which: will the role of doctors be readdressed? will my tasks be revisited?

In my view, I believe there is no right answer for such questions, but what I surely know is that the change or upgrade is coming and the right thing to do is to get ready to embrace it for one simple reason which is:

AI will bring patient care to new heights and for me thats all what matters!

If you ask me what's in it for me as a healthcare professional? I would ask back what's in it for the patient.

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Educators practices of yesterday, look different than educators practices of today, and will look different than educators practices of tomorrow. The means, settings, interactions, and even curriculum looks different. The whole learning journey looks different from just over a decade ago.

Artificial intelligence and advanced technologies have been a game changer to the education sector.

Artificial Intelligence brigs on value to educators, students, and institutions. The pandemic caused a major shakeup on the education sector, among the chaos one positive emerged – getting closer to advanced technologies. Institutions placed tremendous work by exploring various technological applications in the effort of finding the best fit to their practices.

One major challenge we faced is the lack of preparedness and talent in the space to take immediate action.

In my experience the use of technologies have been very much helpful. First, applying collective intelligence tools for grading automation in multiple or selection choices. In my opinion grading can be tedious and is considered lost time for any teacher, although text grading is still far from realization. Automation large sections of an exam allowed me to use the saved time for better student interaction and lecture preparation. Second, academic research data crunch efforts using advanced analytics software's. Third, I have used AI to apply some sort of individualized learning I believe this will require more effort by developers but I have no doubt we will reach soon.

Many academic institutions are embracing AI; however most institutions lack a clear organizational data strategy which is a key enabler for AI which makes me believe that the pace will face unnecessary delays.

My last suggestion for scholars and educators is to have a change in mindset and open up to new possibilities paused by artificial intelligence.

Good news alert: the academic community cannot be replaced by robots but merging efforts can only have tremendous value!


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