Technology can be defined as the application of scientific knowledge for practical purposes, especially in industry (Stevenson., 2010). This is commonly manifested in equipment developed from this application and in turn, has provided us with new roles within a range of fields.

Careers within technology are no longer restricted to the traditional and/or stereotypical foundations. We have now seen a widespread increase in technology spanning across a range of industries, from retail to medicine to medical equipment. Within these areas we see roles that include but are not limited to, data scientists, who are responsible for analysing and interpreting large amounts of complex data; software engineers, who create, maintain and improve systems; and machine learning engineers who develop and apply algorithms that adapt and improve automatically through experience (McGraw-Hill, 1997).

Developments in technology continue to progress in many aspects of everyday life. A key example of this is the emergence of self-driving cars, smart homes and immersive virtual reality gaming. This progression is also reflected within the job market. In 2019, UK tech investment grew by 44% to a record £10.1bn and tech employment grew by 40% in the last 2 years (TechNation, 2020).

Due to COVID-19, there has been a sharp increase in stocks in the online retail market. Adobe Analytics (currently only using US data) reported an additional $107 billion dollars to have been spent online since March. To put this into context,  ⤴

in 2019 US consumers had only two $2 billion days outside of the holiday season. This year, we have surpassed that milestone in August and have already had 130 days. We also see this surge in companies that utilise the digital platform like Zoom. Creator Eric Yuan revealed in a blog post that in March 2020 they were seeing 200 million daily meeting participants and 300 million in the following month. To put this into context again, in December 2019, Zoom would see 10 million meetings. Some may argue that this is a temporary change, and solely as a result of the current climate. And while it remains clear that these stocks/values will not remain at these peaked heights, it is sensible to assume that their dominance will persist. Not only due to the COVID19 pandemic, but also because of the continual but also because of the continual and progressive integration of technology within our daily lives. It is the latter that will push companies and business’ to make a shift and adapt to an increased digital market and workspace.

While the fundamental progression of technology poses a minimal threat, it is the biases behind the development that are detrimental to particular demographics in society. This report very briefly touches upon this topic, and highlights some of the repercussions as a result. This report is not a solution, and will not provide you with the answers to this problem. There are professionals who are experts in this field and are there to provide you with the support. Research them, use them, and then pay them for their skills.

This report very briefly touches upon this topic, and highlights some of the repercussions as a result… There are professionals who are experts in this field and are there to provide you with the support. Research them, use them, and then pay them for their skills.

In recent years, rapid development of technologies have overtaken conversations around the ethical implementation of them. While there have indeed been conversations around ‘just because we can do it, does it mean we should?’, we have not progressed in formalised or legal implementation around some of these assets.

An example of where technology advancements has preceded the ethical considerations is in the creation of the gene editing technology, clustered regularly interspaced short palindromic repeats (CRISPR). CRISPR is a protein that can be used for genome editing, it can alter the DNA in any cell, organism, plant cell (Bernabé‐Orts et al., 2019) and even in human cells (NPR article – Stein, 2019).

Gene editing in humans is currently illegal in the U.K. as reviews of the technologies’ ethical considerations and the potential repercussions of legalising it is an ongoing discussion (Nuffield council on Bioethics, 2018). Key issues surround the fact that very small changes to humans and wildlife can cause changes throughout the whole ecosystem. Potential repercussions have the ability to change life in itself for everyone, this includes the extinction of animals that interacted with said species. Another ethical dilemma is nested within scenarios that question our empathy towards others life and living conditions. For example, it is agreed that the spread of malaria through mosquitos is bad and with CRISPR we have the potential to eradicate this problem and save lives. We can also apply this logic to human gene editing, for example, editing genetic make-up to provide someone with a better quality of life that is equal to everyone else or even for survival. Most would agree this is beneficial to the individual and society. Because steps can be taken in this direction, ⤴

it is important to discuss the intricacies regarding what it means to provide individuals with a better quality of life, versus desired cosmetic changes (an extreme example is choosing a child’s eye colour). Arguably, the worst-case scenario is in societies tainting of and deeming particular characteristics as negative and undesirable. And in turn, using the technology to eradicate these characteristics potentially leading to a new eugenics movement. On reflection of past eugenic eras, one resolution is proposed by Aultman (2006). It emphasises the need for researchers to move away from the traditional view, that looks at how their research will benefit society. And move towards reflecting on past ethical and moral injustices that can help anticipate the potential misuse and misinterpretation of knowledge disseminated (Daramy, F., 2020).

Such important and life changing ethical discussions require and demand the power that is in the diversity of thought. Exploring these topics from a range of perspectives, knowledge and life experiences is crucial in the development of every societies’ future. Including those that do not interact or use technology. Having a diverse group of individuals provides insight into topics and issues that a group of like minded individuals would not consider. It not only provides perspective but, also growth for companies and society as a whole. The BBC would have benefitted from this when the board decided it would be okay for their presenter to use the n-word at 10:30am on Wednesday 29th July 2020 and again on Saturday 1st August 2020. The BBC responded to the 18,656 complaints by stating that they had conferred with the board members about whether it was the correct decision (please Google those board directors). Over the course of a week and a half, it then took 384 Ofcom complaints and a Radio1 DJ quitting for them to apologise.

Having a diverse group of individuals provides insight into topics and issues that a group of like minded individuals would not consider.

Other ethical considerations surrounds individual’s personal data, the use of it and ownership. In 2018, Cambridge Analytica (CA), a political consulting firm, was investigated for the misuse of personal data from Facebook during political campaigns. Briefly, CA used Facebook user’s information to influence US, U.K and many other countries political elections. With user’s personal data, they categorised people into polarised leftwing, polarised right-wing and the ‘persuadables’. If you were a part of the persuadable population (or was someone who was on the fence), you would be targeted with personal advertisements that would favour said election party and to disregard the competition. In 2016, CA joined the Trump campaign and also worked for leave.EU during the European Union referendum. By bombarding users with tailored advertisements to discredit the opposition, the company held the ability to sway users’ thoughts and behaviours at an individual level.

This misuse of data presents concerns of manipulation and creates a distrust within society. This is something that is rapidly progressing in the background through machine learned algorithms. They are designed to cater your news feeds with information that is specific to your likes as opposed to the truth. We also see issues with data in terms of the lack or loss of it. We know that Black women are one of the most underrepresented groups within our societies however, we are unsure the extent of this. This is because of how the statistics are collected and collated. Irrespective of job or field, the statistics on representation are often categorised and reported as ‘women’ and ‘ethnic minorities’. ⤴

As a result, we often lose data on females of ethnic minorities within the two overseeing categories. For example, in the context of academia, we know that on average, female professors earn 6.3% (£4,828) less than their male counter parts (UCU Report). And Black professors earn 9.4% (£7,147) less than their white counterparts but, what does this mean for Black women? A recent report revealed that there are only 25 Black female professors in the UK. This is in comparison to 4000 white female professors and over 12,000 white male professors. The lack of data on Black women means that society is unable to adequately discuss this issue, leading to the problems faced by this group of people to be essentially ignored by the masses. The developments in technologies are often a representation of the creators. As discussed by Jordan Harrod during #BlackInNeuroWeek2020 in our #NeuroRacism panel (Tuesday, 28th July 2020), we are aware and understand that technology and/or algorithms themselves cannot be racist however, there are racial biases within the data. Some of these biases are a result of the lack of representation in the conversations. The individuals that develop these technologies are often white males and so, the technology is designed around the needs of a population that fit into this description. With an unequal starting point, the algorithms continue to redefine and perpetuate a blueprint of information from that particular demographic. While this may be unintentional in some cases, it nonetheless has an effect on populations that do not fit into this criteria. This is demonstrated in the poor or no recognition that automatic hand sanitisers have with Black hands and also facial recognition ID. More detrimental repercussions are within algorithms that are used to decide where to deploy police officers and who is likely to commit a crime (McGrory and Bedi., 2020).

The lack of data on Black women means that society is unable to adequately discuss this issue, leading to the problems faced by this group of people to be essentially ignored by the masses.

This is not a thing of the past, or of a different generation. The lack of diversity in technology is a very real problem that is here today and will remain until change is demanded. We will continue to see the development of products and services that are not representative of the general population, and that will have negative biases towards certain populations, which is commonly Black communities.

I can only provide you with the statistics and facts, and ask you the reader to think about what this means for Black people. ⤴

It is important to focus on the pattern in the data and the implications of it. Technology will continue to progress and we need to make sure that the conversations and development are inclusive.

Follow the #BlackInDataWeek on Twitter that is coming up (November 16-21st 2020), to connect with Black computer scientists from a range of backgrounds. There are also initiatives such as BlackGirlsCode and Stemettes that have been set up to introduce younger generations to technology and to help learn and build these skills.


  • Aultman, J. M. (2006).
    Eugenomics: Eugenics and Ethics in the 21 st Century. Genomics, Society and Policy, 2(2), 28–49.
  • Daramy, F. (2020)
    Measures of DNA variation may predict variation in cognitive traits, education and life outcomes. What ethical issues does this present to society and how should they be solved? Birkbeck University of London.
  • Mitchell, T.M. (1997)
    Machine Learning. McGraw-Hill, New York.
  • Stevenson, A. (2020)
    Oxford Dictionary of English. Oxford University Press.

About the author

Clíona Kelly is a Black neuroscience researcher at the ALIVE and Cybernetic lab in Birmingham, U.K. She is currently combining virtual reality (VR) and electroencephalography to investigate non-verbal social cues when collaborating with a virtual human. Specifically, she investigates the process of joint attention, which is commonly seen as a difficulty in individuals with Autism. Clíona aims to encourage the use of VR in scientific research but, also to inspire younger Black generations to get involved in technology and change the stereotype of what a scientist looks like.

Connect with her through Twitter and Instagram