Harnessing GIS for Transparent Rental Housing in Beirut

The Beirut Urban Lab, a university research lab in Lebanon, has created an online platform called the City of Tenants to address the lack of transparency in the rental housing market in Beirut. The platform utilizes GIS technology to map rental information contributed by tenants, providing access to data on rent prices and neighborhood characteristics. The database, called the Beirut Built Environment, includes detailed information about the city’s infrastructure.

Through ArcGIS Survey123 and ArcGIS Experience Builder, tenants can anonymously contribute data on rental conditions, such as occupancy status and housing costs. The collected data is used by researchers and policymakers to understand urban trends and develop responsive public policies. The platform aims to empower tenants by providing them with readily available rental market data, helping them make informed decisions and negotiate more effectively. The Beirut Urban Lab plans to expand the platform to other cities in Lebanon and automate data updates through ArcGIS Survey123.


A new era in publishing is on the horizon with the launch of GPT-4, the most advanced AI system created by OpenAI. This revolutionary technology is expected to transform various aspects of society, including academic publishing. However, the integration of AI in manuscript preparation and peer review raises ethical concerns that need to be addressed.

In academic publishing, peer review is a crucial process that ensures the quality and credibility of published work. With the advent of AI, the peer review process could become faster and less laborious, but it also raises concerns about the potential for identical reviews and the lack of field-specific critical input. To address this, journals could potentially ask reviewers to declare the extent to which AI generated the review.

The implications of AI for authors and academic institutions are also significant. The availability of software to create figures and text could make manuscript preparation faster and less labor-intensive, but it also raises questions of originality and ownership of creative work generated by AI. It is crucial for authors to remain vigilant and take steps to mitigate any potential bias. Transparency is key to addressing these issues, and it is essential to declare the involvement of AI in manuscript preparation.

The integration of AI-powered image analysis could enhance the process of assessing whether a submitted article is original, while also making the identification of suitable reviewers faster and more effective. These additional features would be a boon to busy academics who serve on editorial boards.

In conclusion, the advent of AI in publishing is a game-changer, but it needs to be balanced with ethical and transparent use. Editorial boards will need to make rapid decisions on how best to respond to ensure they act responsibly for authors, reviewers, and readers. The future of academic publishing is bright, but it will require careful consideration of the implications of AI for all stakeholders.