In this post I want to talk about FLOSS features and how impactful it is on the open source community. I will also delve into any future implications of FLOSS feature and its advantages and disadvantages.
WHAT IS FLOSS?:
FLOSS stands for Free/Libre and open source software protected by copyrights or patents.
FLOSS has developed from individual programmers to commercial enterprises and communities of coders.(Zimmermann, Jullien, 2006)
Key areas of FLOSS’s development include improved interoperability, security, and collaboration among (FLOSS) projects.(Sayer, 2008)
It focuses off open source software from a collaborative point of view, making it available and accessible to the public, regardless of anyone’s background or needs.
ETHICAL ISSUES:
As impressive FLOSS is to collaboration and the open source community there are some ethical issues that need to be considered.
Some of these being inclusivity and diversity, as FLOSS is technically accessible to the public, this is not promoted enough, which may mean participants may not feel as welcome to contribute to the community.
One is example involving bias and performance issues within this is fully-developed facial recognition model in 2019 for law enforcement in Detroit falsely arrested Robert Williams, a black man for shoplifting. This prediction reached national news shortly after. In the same year, it happened again to Micheal Oliver, who too was African American. (The Gradient, 2021)
This demonstrates how impactful the faults are in these machine learning models, and how accurate and unbiased the data should be.
In order to prevent this in the near future we need to take into consideration that the work evidently aligns with everyone’s values.
IN THE FORSEABLE FUTURE:
Having more research in understanding different FLOSS environments, such as how they are created in different places involves studying how those in communities, companies and governments can collaborate or shape each other and their affect on FLOSS.In addition exploring different ideas about FLOSS and its reputation. Looking into an array of opinions can help with the organisation and development of FLOSS. And finally examining social differences, such as age, gender and other demographics, can affect contribution to FLOSS. This can help us understand more on accessibility and usability. (Lin, 2005)
Looking towards the future for FLOSS features, I believe that if these points are not addressed there can be limited understanding in collaboration. Exclusion from some contributors determined by demographic factors and by ignoring these diverse perspectives, less development, which would decrease the rate of development.
Diverse applications are growing immensely across a range of industries, showing the adaptability of FLOSS.
(Klara Inc., 2024)
By attracting more participants there will be improvements in productivity and accuracy of open source projects relating to FLOSS features, through improvements and more advancements being contributed.
For einsteinpy this can mean that utilising contributions in open source accross friends, especially in settings such as education, government and healthcare can bring a collaborative approach to computer science and astrophysics. This widens Inclusivity and advancements in research relevant to Einsteinpy’s mission can be made.
Overall, FLOSS has major capabilities to attract more contributors toppers source projects, which expands the community, and bring a larger array of outlooks, raising awareness on any ethical issues or highlighting other users’ needs from the project.
REFERENCES:
Zimmermann, J.-B. and Jullien, N. (2006). Free/Libre/Open Source Software (Floss): Lessons for Intellectual Property Rights Management in a Knowledge-Based Economy. [online] Ssrn.com. Available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=953187 [Accessed 24 May 2024].
Sayer, P. (2008). FLOSS roadmap, destination 2020. [online] InfoWorld. Available at: https://www.infoworld.com/article/2077949/floss-roadmap–destination-2020.html [Accessed 24 May 2024].
The Gradient. (2021). Machine Learning, Ethics, and Open Source Licensing (Part I/II). [online] Available at: https://thegradient.pub/machine-learning-ethics-and-open-source-licensing/ [Accessed 5 Jun. 2024].
Klara Inc. (2024). 8 Open Source Trends to Keep an Eye Out for in 2024. [online] Available at: https://klarasystems.com/articles/8-open-source-trends-to-keep-an-eye-out-for-in-2024/ [Accessed 8 Jun. 2024].
Lin, Y. (2005). The future of sociology of FLOSS. First Monday. doi:https://doi.org/10.5210/fm.v0i0.1467.