Eportfolio

Collaborative discussion 1: Codes of Ethics and Professional Conduct

Initial Post

Case study: Medical Implant

This report evaluates the alignment of Corazón's operational practices with the British Computer Society (BCS) Code of Conduct (British Computer Society, 2022) amidst discovering a security vulnerability in their heart health monitoring device.

Public Interest: Corazón's initiative to enhance cardiac health monitoring is congruent with BCS's mandate for public welfare, particularly in extending access to disenfranchised populations were fostering IT inclusivity.

Professional Competence and Integrity: Corazón's adherence to established cryptographic protocols and collaborative vulnerability assessments underscore their commitment to professional development and ethical rectitude, eschewing tasks beyond their expertise and in line with best practices in the industry (Khan et al.,2020).

Duty to Relevant Authority: Corazón's regulatory compliance and proactive response to the identified security flaw demonstrate a diligent fulfilment of their obligations to governing entities without any deceptive representation of the product performance.

Duty to the Profession: Corazón evidences their dedication to elevating industry standards and maintaining the IT profession's integrity through an active bug bounty program and transparent engagement with the security community.

Legal and Social Implications: Despite ethical diligence, the identified vulnerability underscores the imperative for rigorous risk management and legal readiness to address potential adverse incidents, as recommended by Noah (1994).

Professionalism and Continuous Improvement: The professionals at Corazón exemplify ethical conduct through critical engagement with security experts and adherence to non-discriminatory practices, mirroring BCS's codes of equality and professional advancement.

In summary, Corazón's practices largely accord with the BCS Code, with their vigilant and ethical approach towards medical technology deployment and data security. Nonetheless, the embedded hard-coded value necessitates continuous risk reassessment and the pursuit of the highest professional standards to mitigate emergent vulnerabilities.

References

British Computer Society (2022) Code of Conduct for BCS Members. Available from: https://www.bcs.org/media/2211/bcs-code-of-conduct.pdf [Accessed 14 November 2023].

Khan, M. N., Rao, A., and Camtepe, S. (2020). Lightweight cryptographic protocols for IoT-constrained devices: A survey. IEEE Internet of Things Journal, 8(6), 4132-4156.

Noah, L. (1994). The imperative to warn: Disentangling the right to know from the need to know about consumer product hazards. Yale J. on Reg., 11, 293.

1st Reply:

Hi Ruth,
The case of abusive workplace behaviour you presented, precisely Max's discriminatory actions, underscores a flagrant violation of both legal statutes and professional ethical codes. Furthermore, the systematic exclusion of female team members from scholarly publications constitutes a breach of the UK's Equality Act 2010, as you rightly argued, encapsulating direct discrimination and harassment—actions that contravene protected characteristic provisions (Government Equalities Office, 2010).

Max's refusal to permit Diane's participation in a team presentation further engenders a hostile work environment, exacerbating the gender disparity endemic within the industry, as argued by Tovmasyan and Minasyan (2019). Such behaviour undermines legal obligations and contravenes the ethos of professional conduct delineated by the ACM Code of Ethics and Professional Conduct and the BCS Code of Conduct (British Computer Society, 2022).

Max's and Jean's actions infringe upon principles safeguarding individual dignity and promoting an inclusive professional milieu. The harm to team members and the potential erosion of the sector's reputation epitomize the outcomes these ethical frameworks endeavour to avert. As you rightly argued, it is incumbent upon computing professionals to embody and advocate for standards that fortify the profession's integrity and foster an environment devoid of discrimination and harassment.

References:

British Computer Society (2022) Code of Conduct for BCS Members. Available from: https://www.bcs.org/media/2211/bcs-code-of-conduct.pdf [Accessed 14 November 2023].

Government Equalities Office (2010) Equality Act 2010. Available from: https://www.gov.uk/guidance/equality-act-2010-guidance [Accessed 16 Nov 2023]

Tovmasyan, G., and Minasyan, D. (2019). Gender inequality issues in the workplace: case study of Armenia.

2nd Reply:

Hi Dominic, hi Leigh,
The discourse on Blocker Plus underscores the necessity for a harmonised approach to ethical standards in computing, drawing upon the ACM Code of Ethics (Association for Computing Machinery, 2018) and the BCS Code of (Conduct British Computer Society, 2022). Although neither the ACM nor BCS codes are legally binding, as Leigh has rightly argued, they provide nonetheless a foundational ethical framework that transcends jurisdictional borders and informs professional conduct in the digital realm. Blocker Plus's compliance with U.S. regulations is necessary but needs more for global ethical accountability.

Professionally, the anticipation of misuse and robust security measures are imperative, as delineated by ACM's principle 2.9. Blocker Plus's failure to preemptively secure its model and the subsequent difficulty in rectification suggest a deviation from these ethical expectations. This oversight also contravenes BCS's principles concerning integrity and transparency, which are paramount for public confidence.

Socially, while the objective to safeguard vulnerable demographics aligns with ACM and BCS imperatives, the unintentional censorship due to the corrupted model indicates a breach of principles advocating harm avoidance and anti-discrimination. The reputational harm from such breaches accentuates the social onus on computing professionals to manage risks and communicate transparently and proactively with affected stakeholders.

Blocker Plus's case exemplifies the criticality of enduring ethical vigilance and transparent communication within the computing profession to maintain societal trust and ensure an equitable digital ecosystem.

References:

Association for Computing Machinery (2018) ACM Code of Ethics and Professional Conduct. Available from: https://www.acm.org/code-of-ethics

British Computer Society (2022) Code of Conduct for BCS Members. Available from: https://www.bcs.org/media/2211/bcs-code-of-conduct.pdf [Accessed 10 November 2023].
In reply to Leigh Feaviour

Summary post:

Reflecting on the rich discussions initiated by Dominic, Leigh, Nicholas, and Ruth, it becomes evident that the ethical landscape in computing is complex and challenging. In the Blocker Plus case, Corazón's medical implant scenario, and the workplace discrimination presented by Ruth, we can clearly understand the challenging terrain of balancing technological advancements with ethical imperatives as set out by the ACM and BCS codes (Association for Computing Machinery, 2018; British Computer Society, 2022).

The Blocker Plus case, as highlighted by Leigh and Dominic, illustrates the delicate balance between securing digital platforms and respecting user rights. It reaffirms the necessity for a harmonised ethical approach, upholding professional integrity, addressing social obligations by safeguarding against misuse and ensuring robust security measures. In addition, the discussion emphasises that while no system is impervious to attacks, the duty of diligence and transparent communication with stakeholders remains paramount.

In the case of Corazón, we see an embodiment of public welfare through the deployment of heart health monitoring technology. The proactive engagement with security vulnerabilities underscores the commitment to professional competence and continuous improvement. Nevertheless, as Nicholas rightly presented, ethical vigilance must be constant, especially considering potential legal and reputational repercussions.

Ruth's post on abusive workplace behaviour, particularly Max's gender-based discrimination, is a stark reminder of the ethical responsibilities professionals hold towards creating an equitable work environment. This situation aligns with legal stipulations like the Equality Act 2010 and the moral frameworks outlined by the ACM and BCS, which advocate for a discrimination-free industry.

Each case discussed here exhibits the critical importance of upholding ethical standards, not as mere guidelines but as fundaments of our professional identity. As we navigate these ethical dilemmas, it is clear that our actions have far-reaching consequences that extend beyond the immediate scope of our work.

References:

Association for Computing Machinery (2018) ACM Code of Ethics and Professional Conduct. Available from: https://www.acm.org/code-of-ethics [Accessed 27 November 2023].

British Computer Society (2022) Code of Conduct for BCS Members. Available from: https://www.bcs.org/media/2211/bcs-code-of-conduct.pdf [Accessed 27 November 2023].
In reply to Giuseppe Raneli

Discussion Board 2: Case Study: Accuracy of information

Initial Post:

The ethical conundrum Abi, a researcher and statistical programmer, faces in the cereal "Whizzz" case study illuminates vital ethical, legal, social, and professional considerations in scientific data reporting.

From an ethical standpoint, Abi's situation underscores the primacy of honesty in research. The temptation to present data in ways that support contradictory conclusions contravenes the integrity imperative in scientific communication. In "An Introduction to Research Ethics" (1996), Friedman emphasises scientists' moral obligation to present data truthfully and accurately, irrespective of external pressures, whether financial or reputational.

On the legal front, concealing the potential harmfulness of "Whizzz" through selective data presentation could lead to consumer harm, inviting legal repercussions under consumer protection laws. The European Union's procedures against deceptive advertising serve as a concrete example (European Union, 2019).

Socially, the selective portrayal of data could erode public confidence in scientific research, as Nath and Winnacker (2012) argued. Both authors highlight the dual responsibility of researchers towards truthfulness and public welfare.

In this instance, Abi risks the credibility of himself and his institute. The ethical codes of professional bodies, such as the American Statistical Association, underline the importance of objective data presentation (American Statistical Association, 2023).

Abi's obligation extends to presenting both the favourable and unfavourable analyses of "Whizzz" to provide a balanced view. Although he is not directly accountable for misusing his results, he should foresee and attempt to mitigate potential misapplications.

In the event of his suspicion that only positive findings might be publicised, Abi should undergo the following steps:

First, communicate his findings to the manufacturer, underlining the ethical and legal ramifications of selective data representation. Second, include a disclaimer in his report to caution against the misleading nature of partial data representation and, finally, seek guidance from legal or ethics experts at his institute.

In conclusion, Abi's challenge demands balancing professional integrity and client expectations. Ethically, the most defensible action would be objectively presenting all findings, acknowledging the product's potential risks while recognising his limited control over the subsequent analysis application.

References:

Friedman, P.J. (1996). An introduction to research ethics. Science and Engineering Ethics, 2(4), pp.443–456. doi: https://doi.org/10.1007/bf02583931.

European Union (2019). Unfair and blacklisted commercial practices. [online] Your Europe - Citizens. Available at: https://europa.eu/youreurope/citizens/consumers/unfair-treatment/unfair-commercial-practices/index_en.htm [Accessed 17 Jan. 2024].

Nath, I. and Winnacker, E.-L. . (2012). Responsible Research Conduct. Science, 338(6109), pp.863–863. doi:https://doi.org/10.1126/science.1231306.

American Statistical Association (2023). American Statistical Association (ASA). [online] www.amstat.org.
Available at: https://www.amstat.org/ [Accessed 17 Jan. 2024].

1st Reply:

Your post rightly addresses the ethical challenges in research, emphasising the importance of objectivity and transparency.

The references from Bolton (2023) and Berenson et al. (2020) you mentioned rightly underscore the unethical nature of data cherry-picking to fit preconceived conclusions. This practice directly contravenes the principle of scientific integrity, resonating with my initial analysis of Abi's situation, where presenting unbiased findings is paramount.

In addition, you rightly note that Abi, while not entirely responsible for misusing his results, must ensure clarity and transparency to minimise the potential for misinterpretation. This approach aligns with the responsibility of researchers to prevent misinformation and maintain public trust in scientific research.

The suggestion for Abi to report all findings derived from original hypotheses supports the notion of comprehensive and ethical data presentation. This transparency not only upholds scientific standards but also safeguards against selective interpretation.

The research by Fraser et al. (2018) you mentioned highlights the prevalence of questionable research practices, underscoring the necessity for continual ethical vigilance in the scientific community. This context amplifies the importance of Abi's adherence to ethical principles in maintaining the credibility and trustworthiness of scientific inquiry.

In summary, your post and Abi's case study emphasise the critical role of ethical conduct in research. Adhering to these principles ensures the integrity of scientific work and contributes to the reliability of scientific research as a whole.

References:

Berenson, L., Levine, D. & Szabat, K. (2020) Basic Business Statistics: Concepts and Applications. 14th ed. Harlow: Pearson.

Bolton, P. (2023) Research Briefing: How to spot spin and inappropriate use of statistics. London: House of Commons Library.

Fraser, H., Parker, T., Nakagawa, S., Barnett, A. & Fidler, F. (2018) Questionable research practices in ecology and evolution. PLOS One, 13(7), 1-16.

2nd Reply:

Hi Alberto,
Your post makes a compelling point about the intersection of professionalism and ethics in research. The ethical duty to disclose significant findings as in this instance with Abi, both positive and negative, is indeed a cornerstone of responsible research conduct. This concept aligns with the principles described by Marco and Larkin (2000), emphasising the importance of objective and unbiased data reporting in scientific research to maintain academic credibility and public trust.

In discussing Abi's responsibility for presenting complete and unbiased reports, it is essential to consider the broader implications of such actions. Misleading research can propagate false knowledge, potentially leading to harmful outcomes, especially in areas directly impacting public health, as noted by several authors (Coughlin et al., 2012; Vanclay et al., 2013).

Furthermore, as you mention, the ethical challenges in industry-funded research settings are crucial to this discussion. Goldman and Cutler (2002) highlight the potential conflicts between scientific integrity and commercial interests, emphasising the responsibility of professionals to prioritise consumer welfare and scientific truth over personal gain.

In conclusion, your post correctly asserts that Abi's ethical obligation extends beyond professional duties, encompassing a broader societal responsibility.

References:

Coughlin, S.S., Barker, A. and Dawson, A., 2012. Ethics and scientific integrity in public health, epidemiological and clinical research. Public health reviews, 34, pp.1-13.

Marco, C.A. and Larkin, G.L., 2000. Research ethics: ethical issues of data reporting and the quest for authenticity. Academic Emergency Medicine, 7(6), pp.691-694.

Goldman, C.R. and Cutler, D.L., 2002. Pharmaceutical industry support of psychiatric research and education: ethical issues and proposed remedies. In Ethics in community mental health care: commonplace concerns (pp. 209-233). Boston, MA: Springer US.

Vanclay, F., Baines, J.T. and Taylor, C.N., 2013. Principles for ethical research involving humans: ethical professional practice in impact assessment Part I. Impact assessment and project appraisal, 31(4), pp.243-253.

Summary Post:

Abi's ethical dilemma, centred around analysing and reporting data on a cereal product, "Whizzz," can be academically evaluated through several key research papers, as highlighted by Alberto and Leigh in researching the issue. In practice, the dilemma involves whether it is ethical for Abi to present data in a way that supports conflicting conclusions, potentially misleading stakeholders.

Abi's professional integrity mandates ethical reporting of all findings. This stance aligns with Marco and Larkin (2000), who emphasise the importance of objective and unbiased data reporting in scientific research for maintaining academic credibility and public trust. It is also a core finding of all posts in the forum.

The risks of publishing misleading research, which can grant undue credibility and misinform future research and decision-making, as argued by Alberto in his insightful post, especially in health-related fields, are profoundly discussed by several authors such as Coughlin et al. (2012) and Vanclay et al. (2013).

In addition, Abi's responsibility to report both positive and negative findings is crucial for research integrity, considering data's real-world implications, as Goldman and Cutler (2002) discussed and highlighted in several posts in this forum.

In summary, it is ethically obligatory for Abi to report all data objectively, upholding scientific integrity, professional credibility, and public trust. This approach is essential in scientific research and is supported by the research literature on ethics and professionalism.

References:

Coughlin, S.S., Barker, A. and Dawson, A., 2012. Ethics and scientific integrity in public health, epidemiological and clinical research. Public health reviews, 34, pp.1-13.

Marco, C.A. and Larkin, G.L., 2000. Research ethics: ethical issues of data reporting and the quest for authenticity. Academic Emergency Medicine, 7(6), pp.691-694.

Goldman, C.R. and Cutler, D.L., 2002. Pharmaceutical industry support of psychiatric research and education: ethical issues and proposed remedies. In Ethics in community mental health care: commonplace concerns (pp. 209-233). Boston, MA: Springer US.

Vanclay, F., Baines, J.T. and Taylor, C.N., 2013. Principles for ethical research involving humans: ethical professional practice in impact assessment Part I. Impact assessment and project appraisal, 31(4), pp.243-253.

Reflective Piece

Reflective Essay: Revisiting Research Methods and Professional Practice in Data Science

As a full-time trader, embarking on the Research Methods and Professional Practice module as part of my Master's in Data Science journey has been both a nostalgic and enlightening experience. Having previously completed a similar module during my MBA, I anticipated a simple refresher. However, the depth of insights and the nuanced approach tailored for data science have reignited my appreciation for research methodologies' academic rigour and complexity. This reflective essay will summarise my journey through the module, highlighting the valuable lessons learned, challenges overcome, and the practical application of these insights in private trading.

The personal return to research methodology can be compared to visiting a known place and discovering new facets of the location. In addition, the process of creating a research project, primarily through the lens of data science, offered a unique perspective on the following subjects:

1. The research onion by Saunders et al. (2023): The model delineates the layers involved in the process, from philosophical stances to data collection and analysis methods. This model, first introduced by Saunders et al. (2007), was a pivotal guide in structuring my research proposal systematically and coherently.




2. Qualitative and quantitative Research methods: Concepts about running quantitative or qualitative research and using statistical models to analyse results and extrapolate new insights reminded me of my previous work and the knowledge I gathered, and they opened new avenues for potential research ideas in fields such as behavioural influences on investing and time series forecasting.




3. Statistical Models: Revisiting statistical models allowed me to delve into new forecasting processes, such as Arima or recurrent neural networks for stock price predictions, which I will apply in my final MSc project.

The mentorship and direction offered by our tutor played a crucial role in understanding the complexities of data science research and properly organising research initiatives. In addition, the tutor's deep knowledge fostered a thoughtful and analytical mindset towards developing literature reviews by adding critical reviews and possible future avenues of research. It also provided several ideas for my final project work, and her previous experience in time series forecasting gave me the confidence to use her as my tutor for my final MSc project.

Despite my previous exposure to research methodologies, recalling all the lessons learned posed a significant challenge. The vast spectrum of data science techniques and their applicability to real-world problems required a robust understanding of fundamental and advanced concepts, starting from machine learning for predictive analytics, natural language processing (NLP) for sentiment analysis, and time series analysis for time-series forecasting. Furthermore, introducing new material tailored to data science was crucial in refreshing my memory and reinforcing my understanding of critical principles for creating my research proposal. This process underscored the importance of continuous learning and adaptability in the ever-evolving field of data science, machine learning and artificial intelligence.

The culmination of this module was the development of a research proposal aimed at enhancing personal trading strategies by applying data science concepts to Zweig's (1986) Breadth Indicator Concept in analysing market trends with SP500 future market trends. Combining Zweig's theory and future trends with advanced data science models, I aim to forecast ETFs highly correlated to the Sp500. In addition, the research conducted as part of the literature review provided invaluable insights into market trends, volatility patterns, and predictive analytics, thereby enabling a more informed and strategic approach to trading. In particular, the contrast between the efficient market hypothesis advanced by Fama (1970) and behavioural finance theorists such as Kahneman and the late Tversky (1979) shows that data analysis is required to make informed decisions based on understanding the complexities of market movements and investor behaviour. While the efficient market hypothesis affirms that markets are perfectly efficient and all relevant information is already reflected in stock prices, negating the ability to achieve higher returns consistently, behavioural finance introduces the concept of psychological biases and irrationalities in investor decisions. This divergence underscores the necessity of leveraging sophisticated data analysis techniques to dissect market trends, identify anomalies, and predict future movements more accurately. In doing so, it acknowledges the critical role of empirical evidence in challenging theoretical paradigms and enhancing our strategic approach to trading and investment.

One significant challenge was the solitary nature of undertaking the whole module alone, particularly the inability to join the available seminars due to personal commitments, underscoring the challenges of remote learning. This isolation was mitigated by the module's discussion boards, which introduced a much-needed element of exchange with other students. These platforms allow for exchanging concepts, feedback, and insights, fostering a sense of community and shared purpose. Engaging with peers through these discussion boards broke the monotony of remote study and enriched the learning experience by providing different perspectives and approaches.

Last, a further integral aspect of my journey through the Research Methods and Professional Practice module was grappling with the ethical considerations inherent in data science research, particularly regarding financial trading. Advanced data analytics tools and models carry significant responsibility, significantly when predicting market movements through sentiment analysis and accessing people's comments on social platforms (Garg et al., 2020). Reflecting on the ethical guidelines proposed by professional bodies and academic institutions, I recognised the importance of transparency, accountability, and integrity in conducting research. The ethical framework concepts in the module and discussion board interactions guided my approach to developing a research proposal that seeks to optimise trading outcomes and respects the principles of fairness and honesty in financial markets. Ethical considerations have since become a foundation of my research strategy, ensuring that the pursuit of data-driven insights is aligned with the broader values of people's privacy rights and outcomes broadly beneficial for society.

In conclusion, the Research Methods and Professional Practice module has been a journey of rediscovery, learning, and practical application. It has reinforced my understanding of research methodologies and provided a solid foundation for applying these principles to enhance my trading strategies. Notwithstanding, the challenges encountered along the way have been instrumental in fostering growth and resilience, ultimately contributing to my professional development as a data scientist and trader.

References:

Fama, E.F. (1970). Efficient Capital Markets: a Review of Theory and Empirical Work. The Journal of Finance, 25(2), pp.383–417. doi:https://doi.org/10.2307/2325486.

Garg, S., Panwar, D.S., Gupta, A. and Katarya, R. (2020). A Literature Review On Sentiment Analysis Techniques Involving Social Media Platforms. [online] IEEE Xplore. doi:https://doi.org/10.1109/PDGC50313.2020.9315735.

Kahneman, D. and Tversky, A. (1979). Prospect Theory: an Analysis of Decision under Risk. Econometrica, [online] 47(2), pp.263–292. doi:https://doi.org/10.2307/1914185.

Saunders, M., Lewis, P. and Thornhill, A. (2023). Research Methods for Business Students. 9th ed. Harlow: Pearson.

Zweig, M. (1986). Martin Zweig's Winning on Wall Street. Grand Central Publishing.

Literature Review Reflection

Reflective Piece On The Literature Review Work:

Writing a literature review on the influence of Twitter sentiment analysis on mutual fund investment performance involved delving into several studies and methodologies. As an MSc Data Science student engaged in trading, I embarked on this reflective piece to illuminate the process and insights gained from the first assestment.

Embarking on a literature review journey, I followed the structured approach proposed by Saunders et al. (2023), adopting a positivist stance and a deductive research method to evaluate the impact of Twitter sentiment on mutual fund (MF) performance. I used a mixed-method approach to explore the dynamic relationship between social media sentiment and financial market behaviour.

Navigating several studies, I uncovered significant findings regarding the relationship between investor sentiment and stock returns. Direct measures, such as consumer confidence indices, were found to correlate with stock market returns, with varying impacts across different market conditions. However, the literature review primarily focused on stocks, leaving a critical gap in understanding MF dynamics, which can diverge from individual stocks.

Diving into Natural Language Processing (NLP), I explored various methods and tools employed in sentiment analysis, ranging from lexicon-based approaches to advanced deep learning techniques. The choice of method depended on project requirements, including data nature, desired accuracy, and resource availability, highlighting the evolving landscape of sentiment analysis in finance.

Twitter's emergence as a key player in financial discourse underscores its significant influence on market trends, reflecting the intersection between social media and financial sectors. Studies correlating Twitter sentiment with market indices suggest its predictive value in market trends, albeit with market manipulation and misinformation concerns.

Research in sentiment analysis and its application to MF investment strategies revealed the critical role of both direct and indirect sentiment measures in fund performance. While direct sentiment indexes exhibited robustness, indirect measures required integration with other market factors for practical analysis, emphasising the need for comprehensive sentiment analysis methodologies in MF contexts.

Research in sentiment analysis and its application to MF investment strategies revealed the critical role of both direct and indirect sentiment measures in fund performance. While direct sentiment indexes exhibited robustness, indirect measures required integration with other market factors for practical analysis, emphasising the need for comprehensive sentiment analysis methodologies in MF contexts.

Challenges in sentiment analysis, such as data accuracy and the complexity of financial language, underscored the need for ongoing advancements in AI and deep learning. Future trends hinted at multimodal data analysis and addressing ethical and regulatory aspects of AI applications in financial sentiment analysis.

In conclusion, this reflective piece sheds light on the intricate process of writing a literature review on Twitter sentiment analysis in MF investment performance. The study aims to provide insights into the dynamic relationship between social media sentiment and financial market behaviour, bridging gaps in the existing literature and paving the way for future research.

References:

Saunders, M., Lewis, P. and Thornhill, A. (2023) Research methods for business students. 7th ed., Harlow: Pearson.

Artefacts

How to use this section: All excel exercises are named after the relevant exercise section provided in the word documents provided in module 8 and 9.