Friday, October 16, 2026
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AviAssist launches specialized drone risk assessment course in Africa

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The AviAssist Foundation has launched a specialized risk assessment course designed to help drone operators, regulators, and aviation professionals navigate complex unmanned flight operations across Africa.

Developed at the request of one of the continent’s largest drone operators, the program teaches the internationally recognized Specific Operations Risk Assessment (SORA 2.5) framework established by the Joint Authorities for Rulemaking on Unmanned Systems (JARUS). The course addresses the rising demand for standardized safety procedures in advanced operations, including Beyond Visual Line of Sight (BVLOS) missions, urban air mobility, and critical infrastructure inspections.

Africa’s commercial drone sector continues to expand rapidly across logistics, agriculture, and infrastructure monitoring, with civil aviation authorities in Cameroon, Kenya, Nigeria, Rwanda, and South Africa adopting SORA as the benchmark for compliance and safety. However, aviation experts note that the region still faces a shortage of certified professionals capable of performing comprehensive risk evaluations for complex operations.

Lead instructor and drone safety expert Tom Rehwinkel emphasized that the four-day practical course equips participants to identify operational hazards, design mitigation strategies, and secure regulatory authorizations while maintaining high safety standards.

The curriculum targets Civil Aviation Authority personnel, drone training leaders, and flight operations and compliance managers. Through case studies, practical group exercises, and formal examination, attendees learn to assess ground and air risks, evaluate concepts of operations (ConOps), and compile formal risk assessments.

AviAssist Director Tom Kok highlighted that delivering international best practices tailored to regional realities is vital as the continent shapes its aviation future alongside industry forums like Aviation Africa and the African Drone Forum.

The inaugural edition of the training will take place in Rwanda from November 26 to 29, 2026. Registration details and promotional rates are available through

Should the Press ‘Run Toward’ AI?

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A new book argues that news organizations should enthusiastically adopt AI to improve their journalism. Critics aren’t so sure.

Since it was first published, in 2001, The Elements of Journalism, by Tom Rosenstiel and Bill Kovach, has schooled fledgling reporters in their craft by advocating that journalists adhere to a series of core principles—including that journalism’s first obligation is to the truth; that it is, in essence, a discipline of verification; and that journalists must serve as a monitor of power. In Rosenstiel’s new book, The Next Journalism: How the Press Must Change to Serve Democracy, released last week by Crown, he argues that his intention is to deepen these principles, not to replace them. But his new recommendations tilt in a different direction. Rosenstiel, a professor at the University of Maryland’s Philip Merrill College of Journalism, argues that journalism is “failing democracy” and should “become more focused on helping people live their lives than on merely getting their attention.”

To achieve this aim, he suggests we reframe our traditional understanding of newsgathering, such that professional journalists, the public, and “machines” all have “distinct, essential, and complementary—not competing—roles.” Notably, he writes that “journalism must run toward Artificial Intelligence, not away from it, to make journalism stronger.” As he explained to me last week: “We should be using AI in journalism to make our journalism better, not primarily to make it cheaper.” And, he acknowledged, “it will be a point of friction in the book.” 

But what exactly would it look like to “run toward” AI? One of his suggestions in The Next Journalism is that news organizations, with the help of AI systems, serve their audiences by assembling “the vast array of public data about community life into a new and easily usable Civic Internet.” In other words, instead of using datasets for one-off enterprise stories, journalists should work to combine multiple streams of information into a single, constantly updating hub—taking on the role of data wranglers, one might say—and then enable audiences to navigate that resource themselves, for instance with an AI chatbot. This, he argues, could help put newsrooms back at the center of their communities. The idea is about “extending the reach of human journalism using technology as a tool,” he told me. “I’m not advocating having AI write stories.”

Rosenstiel gives other use cases for AI systems: auditing reporting to ensure under-covered communities are well-represented; identifying false claims from politicians that could then be fact-checked; collecting and analyzing data about audience needs and preferences. “AI is going to happen. It’s the next digital revolution,” Rosenstiel told me. He acknowledges problems around hallucinations, bias, environmental concerns, and so on. Even so, he argued, models are getting better all the time. And: “If we say, ‘AI is bad, I don’t want to use it,’ it will happen to us.” Without serious journalists getting involved, he said, bad practitioners will move into the space, promising news without the professional ethics or standards of serious journalistic organizations. “That’s why we have to run at it, and run at it with the concept of: How do you make it better?”

Some news organizations are headed in that direction. The Washington Post (Ask the Post AI) and Financial Times (Ask FT) have made chatbots from their journalism, and Jim VandeHei, the cofounder and CEO of Axios, talked to Issie Lapowsky for a recent CJR story aboutAxios’s partnership with OpenAI and what he views as its potential to “save local news.” Many big publishers are cutting licensing deals with tech firms. 

But the idea of embracing AI is harder to swallow for others. In March, Emily Bell wrote for CJR about how a group of news organizations—some from opposite ends of the political spectrum, like The Guardian and Telegraph—have formed the Standards for Publisher Usage Rights, or SPUR, to advocate for guardrails around responsible AI use, among other things. It was encouraging to see an American company, the Associated Press, join SPUR in July, particularly in the absence of political will in the United States for a conversation about meaningful regulation (as in the European Union’s landmark AI Act). Meanwhile, where journalists feel their companies are not taking the troubling aspects of AI seriously enough, as Riddhi Setty reported for CJR in April, unionized employees are fighting for contracts that set terms for its use.

Newsroom opposition to hasty AI adoption comes amid high-profile inaccuracies and citation problems from large language models (LLMs)—which surely break Rosenstiel and Kovach’s rule about journalism’s first obligation being to the truth—as well as a litany of disputes with tech companies over copyright infringement. (These are helpfully collated in the Tow Center’s AI Deals and Disputes Tracker.) “I do not understand this idea that journalism should rush toward AI, particularly in the editorial process,” Courtney C. Radsch, the director of the Center for Media and Digital Governance at the Open Markets Institute, told me. She pointed out that “now you have information operations targeting LLMs” from state actors such as Russia, as Wired has reported, as well as “ideological biases embedded in the LLM,” the impacts of which are difficult to identify. “I mean, sure, do it in your admin functions,” Radsch said. “But the idea that we can use it in the creation and production of journalism, I think, is very problematic—because then what differentiates journalism from anyone else who uses an LLM to create content?”

Felix M. Simon, a research fellow in AI and digital news at the Reuters Institute for the Study of Journalism, found, in a report for Aspen Digital in March of last year, that there is now a premium on distinctive, human-made reporting that cannot easily be made or replicated by AI systems, such as original investigative reporting, nuanced analysis, and stories that come from long-term relationships with communities. Simon told me that some publishers are now thinking, “We have to provide something that is unique, that people cannot easily get elsewhere, and that people are willing to pay for.”  

Simon also looked at how European news organizations are approaching the implementation of AI systems, concluding that there is “incremental” adoption rather than “revolutionary transformation.” (The report grew out of a gathering of about eighty UK and European media leaders who discussed their companies’ approaches to AI.) Most news organizations have focused on efficiency, the report found, and “on automating routine tasks like transcription, translation, and headline creation.” Simon characterizes their attitude toward AI as “a mixture of caution and excitement, with the latter seemingly more pronounced at the senior leadership level.” 

Overall, Rosenstiel’s book contains interesting ideas about equipping journalists for the twenty-first century. He calls on news organizations to better understand the role their reporting plays in the daily lives of the communities they cover, as well as to collaborate much more intentionally with audiences. That is all very welcome. But the most sensible approach to AI tools for news organizations may be the one they’re already taking—not running toward shiny objects but walking around them, cautiously, and verifying whether they’re worth it.

This piece was produced with support from the Craig Newmark Center for Journalism Ethics and Security.

Casablanca Amazigh Theatre Festival unveils highlights of 8th edition

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Theaters across the Casablanca-Settat region will host the 8th edition of the Casablanca Amazigh Theatre Festival from September 30 to October 4, 2026, under the high patronage of King Mohammed VI.

Organized by the Tafoukt Space for Creation in partnership with the Royal Institute of Amazigh Culture (IRCAM) and the Regional Council of Casablanca-Settat, this edition commemorates the 25th anniversary of the 2001 Royal Speech of Ajdir, which launched decisive efforts to promote Amazigh language and culture, culminating in its constitutional recognition as an official language in 2011.

The festival will feature productions and participants from Morocco, the United Arab Emirates, Iraq, Palestine, Egypt and Tunisia. A major Moroccan-Emirati cooperation program includes an exhibition of Arab Theatre Authority publications and an academic symposium on documenting Moroccan theatrical heritage.

Highlights include an Amazigh book exhibition showcasing IRCAM publications, a fine arts exhibition, tributes to educator and playwright El Safi Moumen Ali, journalist Dr. Amina Ben Cheikh and artist Haj Mohamed Bougassen (Smouken), and the competition for the National Prize for Amazigh Culture in the theatre category.

Four troupes will compete with 2025 productions: Amziane Theatre Troupe (Nador), Kunstamz Troupe (Tiznit), Khemis’Art Troupe (Khémisset) and Agadir Arts Workshop (Agadir). Additional performances, academic symposia, book signings and specialized workshops in Tifinagh script, media documentation, Amazigh theatrical lexicon, storytelling and body physics will round out the program.

The edition is dedicated to the memory of the late artist Abou Ali Abdelali.

AI threatens traditional legal frameworks and intellectual property rights

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As artificial intelligence accelerates across global markets, developing nations find themselves caught in a complex struggle between adopting breakthrough technologies and preserving legacy legal frameworks. In Ethiopia, this tension is acutely visible across intellectual property (IP), data governance, and national development strategies.

Experts caution that the widespread deployment of advanced AI systems directly challenges long-established legal principles, threatens traditional protections for creators, and exposes deep structural gaps in domestic data infrastructure.

Teshager Dagne, an Associate Professor and the Ontario Research Chair in Governing Artificial Intelligence at York University in Canada, told Capital that modern AI architecture fundamentally threatens the foundation of copyright, patents, and trademarks.

“Throughout the history of technology, how society controlled and steered new technologies determined their utility and direction,” he noted. “Today, AI is challenging established legal frameworks. Copyright and patent laws are being dismantled by artificial intelligence.”

Elaborating on the issue, he explained that an author publishing a book today might find that work ingested into AI training datasets without permission, attribution, or compensation. The system can then generate content mirroring the original work, rendering the author’s copyright ineffective. A similar dynamic applies to patented innovations and trademarks, creating a legal gap where creators and innovators have limited recourse.

As the global AI race accelerates, African nations, particularly Ethiopia, face distinct structural hurdles. According to Teshager, the “data deficit” stands out as the most urgent challenge. While public sector institutions, hospitals, schools, and government agencies hold substantial volumes of valuable data, researchers and domestic AI developers struggle to access it.

“There is plenty of data in the public sector, but there is an infrastructural challenge and no direct pathway for researchers to utilize it,” he explained. “Legally speaking, older statutes remain tied to legacy technologies. When approached, institutions often claim exclusive copyright over public records, which unintentionally curtails and constrains the growth of artificial intelligence.”

This barrier is compounded by the fact that most commercial AI systems are trained primarily on foreign data. When Ethiopian users rely on these tools, the outputs reflect external knowledge frameworks that lack local context, cultural nuances, and linguistic accuracy. Teshager warned that relying excessively on foreign AI outputs rather than localized sources risks eroding credibility and information integrity.

“At the policy and strategy level, the country has an AI roadmap aimed at leveraging technology to solve societal problems at a micro level,” the professor said. “However, realizing this vision requires investing heavily in compute infrastructure and reforming bottleneck laws across intellectual property, data access, and technological development.”

Furthermore, AI development demands significant computing capacity, including specialized Graphics Processing Units (GPUs), secure data storage, and scalable cloud systems—resources that remain financially out of reach for many independent Ethiopian researchers. This constraint extends across the continent, where technological talent is often limited not by skill, but by insufficient access to high-performance computing environments.

While cloud infrastructure is expanding within Ethiopia, broader regional accessibility remains a work in progress. Nevertheless, the country has made tangible investments in foundational infrastructure.

In February 2026, the Ethiopian Artificial Intelligence Institute, in partnership with the UNDP and Addis Ababa University, inaugurated the AI UniPod—a modern facility equipped with specialized laboratories, robotics equipment, high-performance computing systems, and collaborative learning spaces designed to accelerate Ethiopia’s digital transition.

“You cannot isolate AI as a single technology,” Teshager noted. “It relies on an entire ecosystem of information infrastructure, storage, GPUs, and raw computing power. Because these assets are capital-intensive, they remain difficult to access for the majority of local researchers.”

Technological infrastructure alone is insufficient, according to Teshager. Ethiopia must actively cultivate a specialized workforce capable of building models, conducting advanced research, driving commercial applications, and establishing regulatory guardrails. This requires embedding foundational digital literacy and AI concepts throughout the educational system, from primary schooling through university curricula.

Drawing international comparisons, Teshager pointed to Canada, which launched the world’s first national AI strategy in 2017. Canada’s policy emphasizes proactive workforce transition, supporting industry adoption, and mitigating labor displacement through structured retraining programs.

However, international experience shows that commercial integration takes time. By 2024, only 4.7 percent of Canadian enterprises had formally adopted AI technologies, reflecting broader global challenges surrounding specialized talent shortages and implementation costs.

“If there is viable commercial demand, businesses will adapt,” the researcher stated. “When governments invest in developing a highly skilled technical workforce, enterprises are better positioned to integrate AI productively rather than resorting to workforce reductions. Strategic government direction is essential.”

Assessing Ethiopia’s broader readiness, Teshager noted that while a complete evaluation requires continuous benchmarking, regional technology indices consistently highlight areas for improvement. Regional indices such as the Africa Technology Index place Ethiopia behind continental leaders like Egypt, South Africa, Kenya, and Nigeria in digital infrastructure and readiness.

In government AI readiness assessments across the region, Egypt ranks among the leading African nations (51st globally in Oxford Insights’ 2025 index with a score of 57.5), followed by Kenya (65th), South Africa (67th), Mauritius (71st), and Nigeria (72nd). Overall, Sub-Saharan Africa continues to navigate infrastructural bottlenecks alongside steady digital expansion.

“Ultimately, the pace of technology adoption is directly determined by domestic infrastructural capacity,” Teshager concluded.