About: We, as a society, hold beliefs about science that may be romanticized and inaccurate. These ideas can be exclusionary in the way we define a typical scientist and how science is done. These notions about science can also become obstacles for us as a community to perform rigorous, inclusive and useful science, impede us individually in our professional growth, by contributing to unrealistic self-expectations (and therefore poor mental health), and hinder our ability to build supportive academic communities. We hope that these readings will provide you with a starting point to build a more accurate conception of science.

Skill Building

In addition to developing technical skills, there are many equally important soft-skills you will learn as a researcher – skills like reading research papers, communicating at group meetings, writing research papers and rebuttals, and time management. Although you will likely have worked on similar skills throughout your academic and professional life so far, you may nonetheless find it challenging to adapt your current skills to your new research context. The resources below will help you get started. We hope that in going through them, you can shift your focus from outcome to process: you’re a student and you’re here to learn – it wouldn’t make sense if you already knew how to do everything!

• How to read a research paper [link]
• How to conduct a literature search [link]
• How to communicate about weekly progress with your collaborators [link]
• How to give a research talk [link]
• Professor Margo Seltzer’s Tips on Writing a Thesis [link]
• Larry McEnerney: The Craft of Writing Effectively [link]
• How to (and how not to) review a paper:
  • The Ins and Outs of Reviewing – what’s good, what’s bad, what’s ugly? [link]
  • Mistakes Reviewers Make [link]
  • Last minute reviewing advice [link]

Different Professional Paths

While a career in academia may be fulfilling (e.g. What is it like to be a professor in computer science?), when working on a research projects, you will be surrounded by academics, and you may feel pressure to pursue a similar career path. There are of course many career options that are fulfilling, whether in academia, industry, government, or NGOs, and many different ways to use the skills you develop as a researcher. We list some articles here that share perspectives you may hear less frequently from your mentors in hope to help you understand different professional paths:

• Why is it so hard for scientists to talk about leaving academia? [link]
• Most Ph.Ds aren’t professors [link]
• Why it is not a ‘failure’ to leave academia [link]
• The Jobs I Didn’t See: My Misconceptions of the Academic Job Market [link]
• Teaching and Research in Computer Science at Liberal Arts Colleges: Myths and Reality [link]

Power Dynamics and Research in Context

Who decides which questions are interesting, what research is important and what research gets funded? How does this bias the scientific community towards specific types of discourse, and how does this ultimately affect our societal values and community? It is important to be cognizant of what forces shape our scientific communities, to be skeptical of and to challenge pre-existing values to ensure our research does not create or exacerbate disparities in our society. We list some papers below that illustrate these types of power dynamics in scientific communities as a starting point for you to engage with these issues.

• Saving Science [link]
• Computing Technology as Racial Infrastructure: A History of the Present & Blueprint for Black Future [link]
• Beyond Bias: Re-imagining the Terms of “Ethical AI” in Criminal Law [link]
• “Fair” Risk Assessments: A Precarious Approach for Criminal Justice Reform [link]
• Critical Race Theory for HCI [link]
• Invisible women: data bias in a world designed for men [link]

Understanding Research in Societal Contexts

As scientists and engineers we might be tempted to think of the technology we design, along with the intended end-users, as a closed system. This is misleading because our research is embedded in a complex human system (i.e. society) where human values and history shape what research questions we consider interesting and important, and where our intended end-users are one actor in a web of stake-holders that may come in contact with or will be affected by our technology. In order to understand where our research questions come from and gauge the true down-stream effects of our reasearch output, we have to broaden our impact analysis to consider historical, cultural, political and social contexts.

• Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes [link]
• Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass (talk, book via Hollis)
• Algorithms of Oppression: How Search Engines Reinforce Racism (talk, book via Hollis)
• The Filter Bubble: How the New Personalized Web Is Changing What We Read and How We Think (TED talk, book)

Academic Language and Currency

What is academic culture (language, customs, and values)? Who does this culture exclude and undervalue? And who does it include and award credit and recognition? As members of the academic and scientific communities, it is important for us to think about these questions, and examine our notions of meritocracy and individual excellence. Below are some resources to help you get started thinking about these issues.

• “The Pursuit of Collective Intelligence”, a Talk by Professor Radhika Nagpal
• The Matthew Matilda Effect in Science [link]
• Silent Technical Privilege: As a novice computer programmer, I always got the benefit of the doubt – because I looked the part [link]
• Defensive Climate in the Computer Science Classroom [link]
• Et al. for all: Citations as a Tool for Racial Equity, Inclusion, and Justice [link]
• Racial and ethnic imbalance in neuroscience reference lists and intersections with gender [link]
• The myth of the lone genius [link]
• The Disappeared: Beyond Winning and Losing [link]

Problems with Publishing

Publications and citations serve as a form of currency in academic communities. As such, as academics, we often entangle our sense of self-worth with our publishing record. The publishing and peer-review processes are far from perfect, and we believe that understanding their pitfalls will help you disentangle your sense of self-worth, from the quality of the work you produce, and from the peer-reviews and publishing record of your research (whether good or bad).

• The NeurIPS experiment (2014), and a recent retrospective
• Misinformation in and about science [link]
• Publish or perish: Where are we heading? [link]
• The Journey of a Complaint at SIGCOMM HotNets 2020 [link]

Mental Health in Academia

Even with a supportive research advisor and community, the research process is intellectually and emotionally challenging; it often forces us to re-examine our closely-held beliefs and can challenge our sense of identity. And while the process may lead to growth, it may also lead to struggle. We want to normalize the struggles that research students face, as well as the practice of openly discussing these struggles and seeking help. We hope that some of these resources can help with understanding mental health challenges in academia.

• The Ph.D. Experience: A review of the factors influencing doctoral students’ completion, achievement, and well-being [link]
• Surprisingly Happy to Have Helped: Underestimating Prosociality Creates a Misplaced Barrier to Asking for Help [link]
• Empowering First-Year Computer Science Ph.D. Students to Create a Culture that Values Community and Mental Health [link]
• Lab Counterculture [link]
• “I Know I Have to Work Twice as Hard and Hope That Makes Me Good Enough”: Exploring the Stress and Strain of Black Doctoral Students in Engineering and Computing [link]
• “Black Genius, Asian Fail”: The Detriment of Stereotype Lift and Stereotype Threat in High-Achieving Asian and Black STEM Students [link]
• For some graduate students, the cost of doing science is their mental health [link]
• Dealing with Social Isolation to Minimize Doctoral Attrition – A Four Stage Framework [link]
• Mental Health in Academia by Fay Lin [link]

We additionally encourage you to find a support network by affinity and interest.

Acknowledgements: This guide is adapted from Yaniv’s offering of CS290 at Harvard.