This monolinguistic approach to communicating science has excluded many researchers, including postdoctoral researchers with doctorate degrees at the forefront of science worldwide. Postdoctoral researchers have been trained to write, think, and analyze. Yet, the communication of science through English has dissuaded them from presenting their work, networking with peers, sharing their knowledge with students, writing research grants, and publishing their work, hindering their progression in scientific careers or withdrawal from science. Does linguistic diversity in science help and make everyone inclusive?

Communication is the basis of any relationship, including the mentor and postdocs working towards a common goal. However, a non-native speaker’s overall training by his/her mentor is almost confined to his/her scientific skill development. Overall growth as an independent researcher is restricted in the early stages of their scientific careers, and if problems persist, it could lead to self-doubt and sadness. Only a few people try to minimize these differences by working twice the amount of time, which could affect their work-life balance, leading to compromises in sound scientific thinking. Can mentors and the institutes support them in overcoming these hurdles?

Lectures, presentations, and publications in scientific conferences and journals are the basic requirements/expectations and an eligibility criterion for a researcher. By the late 20th century, most high-impact scientific journals were published in English, and the non-English scientific journals were ignored or less cited, leading to few biases in the conclusions. According to an article published in Nature in September 2023 [¹], scientists who are not fluent in English cannot publish as quickly as native speakers and spend more time publishing in international journals. Language support from journals is only affordable to some, and the rejection of manuscripts based solely on language was almost 2.5x according to the studies by Amano et al. [¹]. Thus, researchers spend more time communicating than focusing on the quality of the science that was thought, perceived, and experimented with. Can journals/reviewers be more lenient, and language support be more affordable in publishing?

Nearly one-third of the researchers avoid international conferences where the primary language is English and give up on them because they lack confidence. Preparing short, precise presentations requires an in-depth knowledge of English which can be challenging for non-native speakers. They are more concerned about fluency, timing, and presentation in lectures. As a result, they avoid mentoring students, struggle to put across concepts to students, and are unable to capture an audience's attention. These shortcomings could contribute to anxiety, low self-esteem, and a dearth of future opportunities.

Science is continuously evolving but so are the challenges associated with it. As researchers, we always find a way to solve problems. Linguistic diversity in science has been discussed and is in practice in a few countries. However, the English vocabulary has been expanded to accommodate scientific terminologies/phrases worldwide and to make it one common language of communication for science. As a non-native speaker, it’s a double-edged sword because the vocabulary of specific languages cannot accommodate the terminologies/expressions of science, and being unable to communicate in English has left them stranded. Thus, learning the language with the help of mentors/peers who could be of support by having discussions and building their confidence by encouraging them to attend specific workshops for language, which are available online and offline. Postdocs could also take these problems to the advisory committee so that they could have workshops organized in the institution, and experts at the institute could help them. Publishing houses can also revise their guidelines for non-English articles and offer affordable services for editing or translation, especially in international journals. Science conferences worldwide could encourage non-native speakers to address the audience in their language while having simultaneous offline or online translations into English via subtitles. This would encourage more researchers to attend, discuss, and present their work with confidence.

Challenges for non-native speakers might be mitigated if they can come up with constructive solutions. Adapting to the environment by the researcher and bringing a few changes in the communication by the science community makes everyone inclusive, leading to unbiased science and individual growth.

Aravind Parthasarathy, Ph.D., is a postdoctoral fellow in the Department of Medicine at the Medical College of Wisconsin.
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However, the substantial impact of diversifying STEM faculty, particularly at four-year universities, including research-intensive institutions in the United States, can have a cascading effect across all educational levels [ ¹].

Despite the focus of universities and federal agencies on the recruitment of students from underrepresented racial minority (URM) groups, such as African American/Black, Hispanic/Latinx, and Native American/Native Hawaiian/Indigenous individuals, the growth of faculty from URM groups has been sluggish, especially in STEM disciplines [²]. A pivotal element for improving faculty diversity involves having a "diverse pool of postdoctoral scholars." Thus, there is a need to create awareness and strategies that promote the transition of postdocs in URM groups to faculty positions. Apart from this, promoting diversity also requires a focus on including international postdoctoral scholars in tenure-track positions. This involves recognizing and overcoming specific challenges that international scholars may face when pursuing academic careers in the United States.

Elevating Faculty Diversity

A diverse faculty can serve as role models for underrepresented students, inspiring them to pursue academic and professional paths. When surrounded by diverse peers and faculty, individuals are more likely to focus on their abilities rather than potential stereotypes [³]. However, the representation of faculty from URM groups, especially in STEM fields, remains disproportionately low in tenure-track positions. A fundamental element for improving faculty diversity involves having diverse postdoctoral scholars. According to the census in 2020, the racial distribution of postdocs in science and engineering with U.S. citizenship or green card holders is 58% white, 20% Asian, 6.5% Hispanic/Latino, 3.7% Black or African American, 0.23% American Indian, 0.18% Native Hawaiian, 1.8% belong to two or more races while the rest is unknown ethnicity [⁴]. The under-representation of postdoctoral scholars from URM groups is mirrored in the faculty percentages as well, where 73% are white, 11% are Asian, 5.8% are black, 5.3% are Hispanic/Latino, 0.44% are American Indian and 0.16% are Native Hawaiian [⁵]. Therefore, by increasing diversity at the postdoc level, there is a higher likelihood of cultivating a pool of qualified candidates who can progress to faculty positions [¹]. Initiating diversity programs in postdoctoral research positions is a proactive step toward aligning academia with the evolving demographics of society.

Innovating Postdoctoral Pathways to Faculty Roles

Many institutions and funding agencies are committed to diversity and inclusion [¹] [²] [ ³]. Fulfilling these commitments requires intentional efforts that help postdocs transition into faculty [³]. A few initiatives that can be considered are as follows:

1. Actively recruiting a diverse pool of postdoctoral scholars, ensuring that efforts reach and engage underrepresented groups.
2. Developing mentorship programs that pair postdocs with experienced faculty mentors who understand the challenges faced by underrepresented groups and provide guidance on career development and navigating institutional structures.
3. Providing diversity, equity, and inclusion (DEI) training for all faculty and staff, creating a shared understanding of the importance of diversity and strategies to promote an inclusive environment.
4. Designing and implementing professional development workshops, networking events, and collaborations that address the unique needs of underrepresented postdocs.

In addition to the emphasis on URM groups for advancing faculty positions, there is a need to address the strategic inclusion of international postdocs in tenure-track positions. Overcoming barriers to recruiting international postdocs involves addressing challenges such as temporary visas and providing them with adequate knowledge about the U.S. education system. Several potential initiatives include:

1. Advocating for more accessible and streamlined visa processes and providing support for visa applications [⁶].
2. Developing orientation programs and resources that can provide information on academic expectations, professional development opportunities, and networking within the U.S. academic community.
3. Organizing networking events, conferences, mentorship programs, and workshops that facilitate interactions between international postdocs and established faculty members, creating opportunities for cultural integration and collaboration.

By combining these strategies, universities can actively contribute to the diversification of postdocs and create an inclusive environment, promoting the success and advancement of scholars from diverse backgrounds in the academic workforce.

Nupur Navlakha, Ph.D., is a postdoctoral scholar in the Microelectronics Research Center, Department of Electrical and Computer Engineering at The University of Texas at Austin and is co-chair of the keynote/plenary subcommittee and member of the communications subcommittee of the NPA Meetings Committee.

Incorporating AI methods into fast-paced, competitive research environments has boosted efficiency by reducing the time needed to complete mundane or repetitive tasks. Deep ML applications have not only heightened curiosity but also sparked concerns among young researchers and early career scientists about the authenticity, ethics, and relevance of AI use for their research projects.

For example, scientists and young researchers may want to use AI to write and summarize research papers and projects using tools such as ChatGPT, launched in November 2022 by OpenAI. ChatGPT enables users to produce and refine responses to queries in specified lengths and formats and incorporate comprehensive literature reviews.

These advances may enable researchers to use AI tools to brainstorm ideas, verify or reject scientific hypotheses, advance current medical diagnostics, predict climate change, and more. The emerging popularity of AI-based tools in research may improve overall productivity in science, especially in the context of economic development through breakthrough innovations. A McKinsey report, The Economic Potential of Generative AI, estimated that AI-based research and development products alone could account for around $320 billion of additional annual revenue across all research sectors. This estimation speaks to the enormous possibility of technological advancement by AI and ML and could simultaneously fill gaps in knowledge faster than current approaches.

Some of the positive impacts of AI implementation in science and technology include but are not limited to automated data acquisition, faster processing time, cost and labor optimization, and providing answers to critical questions that are otherwise difficult to solve. A Nature survey on Artificial Intelligence and Research conducted on 40,000 researchers, published in September 2023, highlighted the enormous benefits of AI in research daily in areas including helping non-native English-speaking researchers in articulating their findings, speeding up administrative tasks, assisting in peer-review processes, generating new hypotheses, and improving overall scientific productivity. Conversely, the negative implications of AI in scientific research may be deeply concerning. As AI challenges existing human standards for proof and truth, significant concerns regarding AI implementation are that it can generate biases and discrimination in data based on inputs. This may result in the production of inaccurate or less reliable data. Moreover, implementing powerful AI and ML algorithms in specific research areas could exacerbate socioeconomic disparities due to differences in levels of training or the possibility of scientific malintent. Additionally, only some universities and research firms have the necessary resources and infrastructure to effectively conduct projects with AI and ML, reinforcing the high expense and exclusivity of implementing sophisticated AI in scientific research.

AI tools are still being developed across fundamental science fields, including information science, mathematics, medical science, geoscience, physics, and chemistry. The recent rise in the use of AI in research suggests a paradigm shift in approaches to address challenges faced in science and technology. Researchers may agree that AI tools are transformative and are here to stay. However, the long-term impact and ethical ramifications of AI utilization will largely depend on the direction chosen by researchers and the scientific community, guided by human intentions, societal responsibilities, and moral principles.

Considering potential ethical concerns associated with AI systems, UNESCO produced the first global standard on AI ethics titled “Recommendation on the Ethics of Artificial Intelligence” in November 2021, later adopted by 193 member states. Central to this recommendation of global AI use are four pillars: protection of human rights and dignity, maintaining harmony among societies, diversity and inclusion, and the sustainability of the environment and ecosystems. The ethical implications of using AI in the STEM field have been carefully integrated into research under various training programs conducted by the National Science Foundation at the institutional level. Ultimately, the larger goals are to harness AI to ethically connect and strengthen the STEM community and foster a positive shift in research paradigms for future scientists and researchers.

Mitali Mishra (she/hers), Ph.D., is a postdoctoral fellow in the Department of Microbiology at the Icahn School of Medicine at Mount Sinai in New York and is a writer/editor for The POSTDOCket.
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Postdoctoral scholars, or 'postdocs,' are at the forefront of this movement and play a central role in steering scientific and technological advancements within healthcare. With their interdisciplinary expertise and steadfast commitment to rigorous research, postdocs serve as catalysts propelling healthcare systems to embrace the transformative potential of artificial intelligence (AI). The groundbreaking work of postdocs not only paves the way for the adoption of AI within the healthcare domain but also facilitates its seamless integration between technological innovation and healthcare evolution, thereby elevating the impact of AI integration on healthcare practices.

Integral to digital health integration is the field of health economics and outcomes research (HEOR), where postdocs play a pivotal role in harnessing the power of AI to analyze vast datasets and identify factors influencing healthcare outcomes. HEOR studies are instrumental in exploring how institutions can reconcile economic efficiency with quality in healthcare delivery. By leveraging AI-powered clinical tools, postdocs significantly contribute to reducing medical errors, thereby enhancing patient outcomes and generating substantial cost savings for healthcare systems. Their active engagement in the digital transformation of healthcare underscores the ability of postdocs to seize opportunities and drive progress in improving healthcare outcomes.

Furthermore, AI-powered tools offer unparalleled opportunities to enhance personalized care by leveraging HEOR data to guide patient outcomes, healthcare delivery, and population health management decisions. By applying predictive analytics models and algorithms, postdocs contribute to identifying risks and benefits, ultimately leading to improved health outcomes and reduced costs. Their expertise in dissecting complex processes serves as a cornerstone in advancing personalized care through the seamless integration of AI.

However, adopting digital technologies in healthcare poses its own challenges, particularly concerning ethical and regulatory considerations. Postdocs are pivotal in shaping policies and guidelines to ensure transparency and responsible implementation of AI-driven technologies. By addressing concerns related to data privacy, bias mitigation, and algorithmic transparency, postdocs pave the way for the ethical integration of AI into healthcare practices.

As the digital landscape of healthcare quality continues to evolve, postdoctoral professionals remain essential drivers of progress, ensuring that AI technologies are developed and implemented responsibly. Through collaborations with clinicians, scientists, and technology developers, postdocs identify opportunities to optimize healthcare quality through AI-powered solutions. Due to the aforementioned reasons, postdocs empower healthcare systems to embrace the transformative potential of AI, delivering more effective and efficient care to patients worldwide while upholding the highest standards of quality and safety. Collaborative efforts between postdocs, clinicians, researchers, policymakers, and patients are essential in navigating complex ethical landscapes, ensuring that these technologies are deployed responsibly and with consideration for patient privacy, equity, and autonomy.

In summary, postdoctoral scholars are instrumental in driving transformative change in healthcare delivery through the seamless integration of AI into healthcare. Through their interdisciplinary expertise, collaborative efforts, and unwavering commitment to rigorous research, postdocs empower healthcare systems to embrace AI's transformative potential, leading to more effective and efficient care for patients worldwide and reshaping the future of healthcare delivery.

Morgan Carson-Marino, Pharm.D., was a 2023 Oak Ridge Institute for Science and Education (ORISE) postdoctoral fellow on the Safety Policy, Research, and Initiatives Team at the Office of New Drugs - Immediate Office, Center for Drug Evaluation and Research, U.S. Food and Drug Administration.