A decolonial approach challenges the assumption that innovation in data science is neutral and argues that ethical considerations are essential for transforming knowledge production and technology development. Rather than viewing privacy, fairness, and bias as limitations, a decolonial perspective sees…

Ethical considerations such as privacy, fairness enable the development of more responsible, inclusive, and impactful solutions. By addressing issues of data protection, representation, and algorithmic bias, researchers can create technologies that better serve diverse communities. In my experience with education…

I believe ethical considerations such as privacy, fairness, and bias do not limit innovation in data science; rather, they drive the development of more responsible, reliable, and impactful solutions. Ethical practices help build trust among users, improve data quality, and…

Hello @Ssemwogerere Brian , Kindly tell us more why you go for YES

I agree. Ethics do not limit innovation; they strengthen it by building trust, fairness, and accountability. Responsible data practices help ensure that solutions are impactful, sustainable, and widely accepted.

In my view, ethical considerations are not a constraint on innovation; they are a catalyst for creating solutions that are more sustainable, trustworthy, and impactful.From my experience working with health information systems and public health data, ethical data management is…

they dont limit innovation, they simply ground it. innovation needs bounded contexts, else if its a bottomless pit, then even value cannot be bottled or used in a manner that can be sustained. Privacy et al are all enabling constraints.…

Benard Ondiek wrote:\"Do you believe ethical considerations such as privacy, fairness, and bias limit innovation in data science, or can they actually drive better and more impactful solutions? Share examples from your experience.\"

Yes

I believe ethical considerations such as privacy, fairness, and bias drive better innovation in data science. By addressing these issues, organizations create more trustworthy, inclusive, and effective solutions. For example, ensuring data privacy and reducing bias in datasets can improve…

\"Do you believe ethical considerations such as privacy, fairness, and bias limit innovation in data science, or can they actually drive better and more impactful solutions? Share examples from your experience.\"

Victor Marshal, BA in Economics and MBA from LSE.. I specialize in Research esp Market Research and Policy development and engagement. Am from Nairobi.. Great to be here

Hi everyone! I\'m Brenda Yankam. I am a Cameroonian, and I reside in Germany. My research interests are the following: Infectious disease modelling, specifically HIV and Tuberculosis; OMOP CDM implementation; and health system strengthening.

Benard Ondiek wrote:Kindly introduce yourself on this section. Kindly include your name, Country, and research interests.Thank you to @all   everyone who has already completed the quiz on the Community of Practice (CoP).As the next step, kindly introduce yourself in this section…

Henrietta Nanyonjo, B.Sc. Human Nutrition & Dietetics with a MSc in Public Health. I am passionate about using data science for resilient public health systems, food systems and food security.