If you’re employed as a data scientist, you must ensure you’re acting ethically on the job.
The truth? Being tasked with analyzing large pools of sensitive information poses a question – can you be trusted with protecting people’s data? By protection, do you actively consider the confidential nature of the information you’re being exposed to? And if so, what are you doing to prioritize its protection?
On top of this, having intimate access to the results of data analysis gives data scientists a great deal of power. Power to inform and influence policymakers, and in this sense, shape the lives of millions of others. Are you equipped to handle this responsibility?
Stay with us as we explore the answers to these questions and more.
Data Science and Decision-Making
As a data scientist, you have the power to impact public policy. How? By sharing the results of the data you analyze with policymakers, you can help shape the direction of the data-led, data-driven policies that are made on our behalf by our governing bodies. If you’ve completed a business analytics masters online, you’ll likely be well aware of this element of your role as a data scientist. This may even have drawn you to this particular career path in the first place.
This is where ethics comes in. Your guidance on data results can affect people’s lives. For this reason, it’s essential that you report the findings of your data analysis accurately, and without bias. This means stating the facts without letting your underlying motives get in the way.
How do you do this? Cultivate a sense of detachment and separation from the data you’re tasked with collating. These are cold, hard facts – black and white, right and wrong. It’s important to remember this, as the results you share will be trusted by the recipients as gospel.
Considering Confidentiality Concerns and Consent
As a data scientist, you’ll have access to large amounts of sensitive data. This can include being exposed to personal identifying information (PII) – such as personal phone numbers, emails, postal addresses, and vehicle registration numbers, to name just a few examples.
So what do you do when you are exposed to this type of information? Consider it confidential. What does this mean? You need the individual’s consent before you release their details – in any capacity. This isn’t just an implied agreement – for ethical data scientists, this is an integral part of their professional moral code. Being sensitive and considerate of people’s data means maintaining its confidentiality, and seeking consent from customers if it ever needs to be released.
Prioritizing the Protection of Sensitive Data
Protection from prying eyes. When your data sources allow you to collect their personal information, they are entrusting you with their privacy. The privacy and confidentiality of the information stored in your databases is paramount, and as such, it must be prioritized above all else.
What does implementation of this look like? It means keeping your database information secure, and away from prying eyes. In this sense, ethical data scientists have a responsibility to keep their database networks secure from external hackers. How? Sensitive data must be protected with top-notch security measures such as anti-virus protection and network firewalls. While it could be argued that instances of hacking are outside of our control, this is simply not the case. If you’re collecting confidential data, it’s your responsibility to protect it. This is data ethics 101.
What does it mean to be an ethical data scientist?
It means not only embracing the responsibility that comes with having access to a large amount of sensitive information but also, respecting and upholding its confidentiality. Privacy is a huge ethical concern for data scientists, and as such, is a top priority.
Another priority? Staying neutral in the face of wielding great power and influence on public policy. Yes, as a data scientist, you have the power to impact and shape the direction of public decisions through the data you share – especially when governing bodies place importance on making data-driven implementations. The ethics of this? Understanding that the information and guidance you provide based on your data analysis can affect millions of lives.
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