Olive oil ‘for peace’ in divided Cyprus

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Workers pick olives in the Greek-Cypriot village of Agios Ioannis, formerly a mixed settlement near the divided capital Nicosia in Cyprus. (AFP)
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Turkish-Cypriot Hasan Siber, left, and Greek-Cypriot Alexandros Philippides, the founders of Coliveoil. (AFP)
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Updated 11 February 2020

Olive oil ‘for peace’ in divided Cyprus

  • Rare example of a start-up bringing together island’s two communities

NICOSIA: In a field bathed in winter light, Hasan Siber patiently harvests his olives. It is a common sight in Cyprus, but his “oil for peace” represents a rare glimmer of hope on the divided Mediterranean island.

Turkish-Cypriot Siber’s oil is to be sold via Coliveoil, a start-up that he founded with his Greek-Cypriot friend Alexandros Philippides.

The pair, in their early 30s, who met at university in London, want to “take the peace process forward” by selling oil from both sides of the island.

“You never know where an entrepreneurial adventure and friendship might lead,” said Philippides.

Based in the buffer zone of Nicosia, the last divided capital in Europe, Coliveoil is a rare example of a start-up bringing together the island’s two communities.

Cyprus has been split since 1974, when the Turkish army invaded and occupied the northern third following a coup aimed at incorporating the island into Greece.

Reunification talks have been suspended since 2017 — but that same year, Siber and Philippides set up their company that same year with the aim to building bridges across the divide.

The project has enthused Siber’s family, some of whom fled the south during years of conflict.

“Working here today fills me with hope,” said Ayhen Eminel, Siber’s retired uncle, who himself tried to set up a bi-communal business in the early 200s but faced rejection by Greek Cypriot authorities.

He uses a rake to pick olives in a sunlit grove owned by Greek Cypriots, in the formerly mixed village of Agios Ioannis.

The septuagenarian, who speaks Greek as well as Turkish, recalls fleeing the Paphos area in southwestern Cyprus after having been a prisoner of war.

Siber’s aunt Sidika Hudaoglu, a primary school teacher in her 50s, said that the project has brought back memories of a childhood spent among the olive groves in the island’s south, which she fled in 1974.

And the entrepreneur’s father Turgut, a 65-year-old cardiologist, has invested in his son’s start-up and has come from Istanbul to support it.

“Working together, it’s the start” of living together, he said.

“I think others will follow . . . It sets an example.”

While bi-communal projects enjoy some support among Cypriots, this one faces several obstacles.

Without a legal framework for registering bi-communal enterprises, Coliveoil has two legal entities, two bank accounts, two phone numbers and two addresses — one of each on each side of the divide.

The company in the south must buy from the one in the north in order to export to the EU.

Complicating the export process is the fact that EU laws are not applied in the self-declared Turkish Republic of Northern Cyprus (TRNC), only recognized by Ankara.

Olives harvested in the TRNC can’t be registered as organic by the EU, even though the pair say that all the olive groves they use are.

“We have to bring down these barriers,” Siber said.

On the northern side of the checkpoint, Siber and Philippides examine olive groves in Meric, a village surrounded by hills bearing a huge Turkish flag visible for miles across the buffer zone.

When they first took olives into the south in 2017, customs officers asked them to clean the northern olives for export to the south, they recall, even though nothing in the European regulations indicates this.

Resolving the Cyprus problem would more than double the island’s overall gross domestic product to €17.4 billion ($19 billion) over 20 years, according to a study by the Peace Research Institute Oslo Cyprus Center (PCC).

But since a summit in Switzerland collapsed in July 2017, there has been no movement in UN-sponsored negotiations for the divided Mediterranean island.

Yet Coliveoil worker Cemre Berk said that she feels she is an active part of the peace process for the first time.

“We’re breaking taboos,” the Turkish-Cypriot said. “The more people get used to seeing Turkish-Cypriots working on the Greek side and vice versa, the more normal it will become.”

Many Turkish Cypriots express regret the outcome of a referendum on a UN reunification plan in 2004 — the year the divided island entered the EU.

Turkish Cypriots accepted the plan, but Greek Cypriots voted it down.

Coliveoil gives 10 percent of its profits to “Home for cooperation,” which houses the start-up in the buffer zone of Nicosia alongside pro-reunificationNGOs.

Jammed between the low checkpoint walls, Coliveoil works with duo CyprusInno, which connects entrepreneurs from both sides of the island.

Such initiatives still attract stigma, says Steven Stavrou, one of CyprusInno’s cofounders, who met his business partner online.

Burak Berk Doluay was the first Turkish-Cypriot he had ever met.

They started their digital platform in 2013 during the country’s economic crisis, and they now count 2,600 members. “It has changed our lives,” said Stavrou, who was also a witness at his associate’s wedding.

“By coming together through business, sometimes things go beyond that.”


Man vs. machine in bid to beat virus

Updated 20 February 2020

Man vs. machine in bid to beat virus

  • Human and artificial intelligence are racing ahead to detect and control outbreaks of infectious disease

BOSTON: Did an artificial-intelligence system beat human doctors in warning the world of a severe coronavirus outbreak in China?

In a narrow sense, yes. But what the humans lacked in sheer speed, they more than made up in finesse.

Early warnings of disease outbreaks can help people and governments to save lives. In the final days of 2019, an AI system in Boston sent out the first global alert about a new viral outbreak in China. But it took human intelligence to recognize the significance of the outbreak and then awaken response from the public health community.

What’s more, the mere mortals produced a similar alert only a half-hour behind the AI systems.

For now, AI-powered disease-alert systems can still resemble car alarms — easily triggered and sometimes ignored. A network of medical experts and sleuths must still do the hard work of sifting through rumors to piece together the fuller picture. It is difficult to say what future AI systems, powered by ever larger datasets on outbreaks, may be able to accomplish.

The first public alert outside China about the novel coronavirus came on Dec. 30 from the automated HealthMap system at Boston Children’s Hospital. At 11:12 p.m. local time, HealthMap sent an alert about unidentified pneumonia cases in the Chinese city of Wuhan. The system, which scans online news and social media reports, ranked the alert’s seriousness as only 3 out of 5. It took days for HealthMap researchers to recognize its importance.

Four hours before the HealthMap notice, New York epidemiologist Marjorie Pollack had already started working on her own public alert, spurred by a growing sense of dread after reading a personal email she received that evening.

“This is being passed around the internet here,” wrote her contact, who linked to a post on the Chinese social media forum Pincong. The post discussed a Wuhan health agency notice and read in part: “Unexplained pneumonia???”

Pollack, deputy editor of the volunteer-led Program for Monitoring Emerging Diseases, known as ProMed, quickly mobilized a team to look into it. ProMed’s more detailed report went out about 30 minutes after the terse HealthMap alert.

Early warning systems that scansocial media, online news articles and government reports for signs of infectious disease outbreaks help inform global agencies such as the World Health Organization — giving international experts a head start when local bureaucratic hurdles and language barriers might otherwise get in the way.

Some systems, including ProMed, rely on human expertise. Others are partly or completely automated.

“These tools can help hold feet to the fire for government agencies,” said John Brownstein, who runs the HealthMap system as chief innovation officer at Boston Children’s Hospital. “It forces people to be more open.”

The last 48 hours of 2019 were a critical time for understanding the new virus and its significance. Earlier on Dec. 30, Wuhan Central Hospital doctor Li Wenliang warned his former classmates about the virus in a social media group — a move that led local authorities to summon him for questioning several hours later.

Li, who died Feb. 7 after contracting the virus, told The New York Times that it would have been better if officials had disclosed information about the epidemic earlier. “There should be more openness and transparency,” he said.

ProMed reports are often incorporated into other outbreak warning systems. including those run by the World Health Organization, the Canadian government and the Toronto startup BlueDot. WHO also pools data from HealthMap and other sources.

Computer systems that scan online reports for information about disease outbreaks rely on natural language processing, the same branch of artificial intelligence that helps answer questions posed to a search engine or digital voice assistant.

But the algorithms can only be as effective as the data they are scouring, said Nita Madhav, CEO of San Francisco-based disease monitoring firm Metabiota, which first
notified its clients about the outbreak in early January.

Madhav said that inconsistency in how different agencies report medical data can stymie algorithms. The text-scanning programs extract keywords from online text, but may fumble when organizations variously report new virus cases, cumulative virus cases, or new cases in a given time interval. The potential for confusion means there is almost always still a person involved in reviewing the data.

“There’s still a bit of human in the loop,” Madhav said.

Andrew Beam, a Harvard University epidemiologist, said that scanning online reports for key words can help reveal trends, but the accuracy depends on the quality of the data. He also notes that these techniques are not so novel.

“There is an art to intelligently scraping web sites,” Beam said. “But it’s also Google’s core technology since the 1990s.”

Google itself started its own Flu Trends service to detect outbreaks in 2008 by looking for patterns in search queries about flu symptoms. Experts criticized it for overestimating flu prevalence. Google shut down the website in 2015 and handed its technology to nonprofit organizations such as HealthMap to use Google data to build their own models.

Google is now working with Brownstein’s team on a similar web-based approach for tracking the geographical spread of the tick-borne Lyme disease.

Scientists are also using big data to model possible routes of early disease transmission.