Qualitative Researcher & Algorithmic Justice
Abstract: This paper regards the discussion of being researcher in the field of Information System as Qualitative Researcher. Later on, a brief summary were added about how can we increase knowledge & awareness on AADM and their algorithmic fairness. Keywords: Qualitative Research, Technical Skills, Information System, Algorithmic Justice
1. Qualitative Research: Research is a systematic and organized process of inquiry and investigation undertaken to discover, analyze, and generate new knowledge, insights, or understanding about a specific topic, problem, or phenomenon. It involves the collection, interpretation, and evaluation of data and information using established methodologies, techniques, and procedures. The primary objectives of research are to answer questions, solve problems, or contribute to the advancement of knowledge in a particular field or discipline. Research can take various forms, including scientific experiments, surveys, case studies, literature reviews, and theoretical explorations, depending on the nature of the research question and the goals of the research endeavor. To the very process of research is to select a topic that genuinely interests thyself and align thy research goals. One must feel passionate about the topic to keep them motivated throughout the process. That leads us to find research gaps and refine research related questions by reviewing literature’s to understand existing theories. If we are answering “Why?” questions, applying observation & interpreting approach to the non-statistical data then we are involved into Qualitative Research. The aim of qualitative research is to understand how an individual subjectively perceives and gives meaning to their social reality that often involves methods such as interviews, focus groups, observations, and content analysis. In order to do that one must familiarize themselves with ethical consideration, selecting participants or subjects carefully by ensuring they represent the population or community which aim to study, develop recruitment strategy & establish rapport and trust to reach the targeted participants. To analyze the qualitative data we can use various coding techniques and thematic analysis to identify patterns, themes, and insights. Software like NVivo or Dedoose etc. can assist in organizing and analyzing data. It is very important to stay current with qualitative research methodologies, theories, and best practices by reading books, journals, and attending relevant conferences or workshops. Proper research report includes an introduction, literature review, methodology, findings,and discussion where writing should be clear to convey the message appropriately. Afterwards peer review can help identify blind spots and weaknesses in the work, so we need to seek feedback from peers and mentors to improve the quality of research. We must know the qualitative research often requires time, patience, and a willingness to adapt our approach as we gain deeper insights into our research field that demands reflecting on our own personalities. It is important to recognize our own biases and incorporate this awareness into the research process, which influences research methodology. Engaging with the community members & participants is important as well as collaborating with other researchers from same field may broaden understanding and give fresh perspective to the research. Additionally, ongoing self-reflection and a commitment to ethical research practices are essential for successful immersion in the field as a qualitative researcher.
2. Technological Skills as Qualitative Researcher: We can enhance the rigor, depth, and relevance of research studies & contribute to the advancement of knowledge and the potential for real-world impact by effectively integrating technical skills into qualitative research. With a solid 12-year background in Computer Science field, I am confident that I possess various expertise in different areas such as Programming, Data analyzing, Computer Network, Security, Artificial Intelligence, Data structures, System analysis, and Database systems. However, without proper utilization, everything becomes useless; so we need to follow strategies by which we can effectively leverage these technical skills into significant directions. To become a qualitative researcher we must need to have proper understanding of the topic we are researching about that requires identify relevant technologies such as skills, tools for specific study areas. To collect data we can use incorporate technologies and to manage them in structured manner we may need to use different technology skills consider using databases or cloud storage solutions, and ensure data security and privacy. Skills like text analysis or natural language processing can be used to analyze large volumes of textual data, extract patterns, and identify themes or sentiments. Afterwards, we have different type of software available like Tableau, Power BI etc. for visualization & live demonstration. Applying user-centered design principles to the research is very effective. For example, we can mix various method of research if needed, engage with online communities and forums to connect with the participants in order to gain clear insights in data collection for ethnographic research. Qualitative studies are essential especially in fields like education or healthcare where we can use Virtual Reality (VR) and Augmented Reality (AR) technologies. One must be mindful of ethical issues related to technology, such as data privacy and informed consent while collecting data from public sources, when integrating technical tools into research. There are various Application Programming Interfaces (API) are available to collect relevant data. To gain access to cutting-edge technologies and methodologies that can benefit research, one must possess better communication skills to collaborate with researchers from different fields related to the study. Staying updated on emerging technologies and methodologies are very important skill that must be groomed time to time. Additionally, attending conferences, publishing academic journals and engaging with different academic communities to have broader audience also included into the list of technical skills. Finally yet importantly is to continuously asking for the feedback from peers, it will always definitely help to enhance the quality of research.
3. Contribute to Information System Research: Now that we have discussed research method and required technical skills, we must know how we can dedicate ourselves into information systems research with them. It is better to have educational background to understand the very core of this context. I already completed the first step as my master’s studies. It is important to keep up-to-date with the latest developments and research trends in information systems, subscribe to academic journals, attend conferences, and follow reputable researchers and organizations in the field. Already I involved myself into these tasks as a preparation for the future adventures. We must know about different research domains within information systems that include topics like data-analytics, cybersecurity, human-computer interaction, decision support systems, or any other relevant area. In order to contribute into these fields a PhD degree or academic research could be the way. I personally believe everything is related to each other & we cannot just focus on one single domain and avoid others. For example, big data-analytic has become the most important part of any research study these days but it is also a field of research itself. Contributing into information system research requires extreme level of patience with the courage of gathering knowledge from anything and everything. I tried to continue my academic interests around information system because my ultimate aim was to contribute into this research area. After that, I have successfully completed many training courses from recognized platforms to gather knowledge. Right present, I have reached a level where I feel liberty to work as a professional in the relevant field where I will be able to use my knowledge properly. Reading and learning about new things are my most favorite leisure that may help me to develop my professional skills more precisely. I wanted to invest on myself first which I’ve been doing successfully over the past years; from being a software developer, I made the journey to become a researcher. I feel very flexible about learning new things, working with team members, asking for help or helping others. The way our modern world is advancing with new technologies we need proper research on information system to make existing systems ideal, dynamic, secure or to invent new. I believe with my knowledge, experience and passion to work into this research area makes me a perfect candidate who can contribute within information system research if given an opportunity.
4. Discussing Awareness of AADM: While the concept of algorithmic justice is aimed at addressing issues of fairness, accountability, and transparency in algorithmic systems, there may be some individuals or perspectives that oppose or express concerns about it. It is important to understand that there are some arguments that can be made against certain aspects or implementations of algorithmic justice, so undoubtedly researchers can raise concerns or considerations about the given topic only. Advocating for algorithmic justice is to support modernization. Discrimination, biasness, unfairness are human attributes where AADM are free from it. Therefore, with time we need to educate ourselves and raise awareness about the potential biases and ethical issues associated with algorithms, especially in areas like AI, finance, criminal justice, and healthcare. Organizations should be encouraged to provide transparency into their algorithmic decision-making processes that treat all individuals and groups fairly and without discrimination. Every inventions requires its own time to reach general people, therefor we must promote ethical AI practices that prioritize fairness, interpretability, and explainability in algorithm design and deployment. Organizations should be accountable for the impact on algorithms in terms of the discrimination. Awareness should be raised into different research groups to come forward and contribute for government policies and regulations that address algorithmic fairness and accountability, especially in critical domains like criminal justice and healthcare. Different communities can be prepared based on diversion & inclusion among the IT industry where they will be able to represent wide range of perspectives. That’s how it would be easier to deal with the problem of being unbiased or biased. IT giants can even organize various training programs to educate next generation IT professionals or non-IT professionals the need of ethics and algorithmic justice. That’s how people would be aware of the situations when they need to report against algorithmic biasness, otherwise things can run smoothly with existing algorithms. Academic research can be helpful to generate modern frameworks for ethical decision-making systems. Open source projects could be added to the existed system for handling projects where discrimination issues raises. Government must play their role into this as fund organizer. In general, awareness should be raised among the communities. Different type of workshops, events or discussion could be arranged to educate people. At modern age, it’s important to be stay informed!
5. Conclusions: Although, I tried to be honest and logical by applying ethical perspectives towards the given issue but I cannot deny few problems that is possible to become threat to our modern civilization. According to my perception, doesn’t matter how modern we become by applying technology to our daily lives, still human beings need to add their emotional strength in decision making which is the main moral behind our long-lasting human society. I agree with the fact that statistical analyzing can lead us to better decision making but AADM does it according to the given scenarios it was trained on but a man does it by making sure how his decision going to affect or effect living creatures. For example, the most concerning red flags arises to this problem regarding security. In order to ensure complete fairness, algorithms are becoming more transparent to everyone that is completely vulnerable from any exploitation. I believe researchers in Information Security may come forward otherwise it may lead to total chaos which is inevitable. Furthermore, as much as we focus on fairness, accountability, and transparency in algorithmic systems we may end up losing autonomy and adaptability of AADM by applying rigid rules & regulation. Much complex system may meet all the requirements but becomes complete failure in various ways such as lack of resources may become burden on start-up business. That brings us to same point from where it has began. We can’t deny the importance of human oversight in critical decision-making processes. To conclude the discussion I would like to mention that it is better to take precaution before we need to find the cure.
References
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[3] Tim Rockt¨aschel et al. Algorithmic Equity: A Framework for Social Applications (2022).
[4] Margaret Mitchell et al. Fairwashing: The Risk of Rationalization (2021).
[5] Aaron Rieke et al. Algorithmic Bias Detection and Mitigation: Best Practices and Policies to Reduce Consumer Harms (2019).
[6] Suresh Venkatasubramanian et al. Fairness and Bias in Algorithms: A Survey (2019).
