During my first weeks in Tampere I experienced the first of May celebrations in Finland also known as “Vappu”. In contrast to some other countries, the first of May is less important for workers’ rights and more relevant for the university students. The night before is often spend partying, while on the day itself everyone joins for huge public gatherings with sweets, picnics and alcohol. Sima a mead like beverage and munkki, a suggar coated donut are typical for those celebrations and sold in small booths all over the city. Freshly graduated students as well as alumni wear their white student cap and every city has its own traditions on what else is organized on the day. In Tampere, students will be submerged into the river running through the city. This is done in the most convenient way possible: by picking up a cage with students by crane. This spectacle is observed by the whole town, who gather at the riverside and bridge to have a look.
Party and picnic at the riverside. Picture by Finn TryggvasonDipping the students into the water by crane. Picture by Finn Tryggvason
The global energy transition towards renewable and sustainable resources has been nudged by institutions such as the UN setting universal standards for social and environmental welfare, and external shocks have questioned the current standards of operation. As they show a pressing necessity to (not only) address issues like climate change, several clusters of organizations, and institutions have started to come together to tackle this challenge.
By “transforming the environmental crisis from a problem into an opportunity” (Fabrizio Di Amato, CEO of Maire Tecnimont during a talk about Leadership at LUISS in Rome), various industries have developed promising solutions like the production of green hydrogen and more.
However, some of these technologies remain costly, and more solutions are needed at a faster pace. The EU has financed and granted several European initiatives like the introduction of hydrogen valleys. Recently, the Important Projects of Common European Interests (IPCEI) (a European Union framework that supports large-scale, transnational projects in strategic industries, like the energy infrastructure) has granted NextChem, an Italian leader in energy transition technologies, and a subsidiary of the Maire Group, 194 € million, as part of the “IPCEI Hy2USE” EU project, for the development of one of the first Waste to Hydrogen plant in the world. The goal of the project is to set up the first industrial-scale technology hub for the development of the entire national hydrogen supply chain.
Projects which include plants like these use specific technologies to transform waste into hydrogen and/or other industrial products and represent a promising solution to address both waste management and energy transition challenges. By converting waste into valuable products, different transformational processes can be applied, and all this, by reducing greenhouse gas emissions, minimizing landfill use, and contributing to renewable energy production.
However, as with other infrastructure projects, like the infamous project of subway building in the Netherlands, they can often be met with community resistance. Concerns about potential impacts on health, the environment, property values, and aesthetics can lead to delays in project approvals, increased costs, and even project cancelations. Coined as the NIMBY syndrome (Not In My Back Yard), communities are often rooting for innovative solutions, as long as they are not close to them.
So, what can be done?
When planning the construction of a plant, the use of digital technologies can limit the environmental impact of the design and experimentation (for example through 3D mappings, like digital twins). But the actual construction of such projects needs strong incentives to attract stakeholders.
Even though this list is not extensive, there are several ways in which companies are adopting a proactive strategy to get various people and institutions on board:
Engaging and including them early on in the decision-making process by maintaining openand transparent communication throughout the implementation and activity of the project.
By collaborating with research institutions and other leaders in the field, projects can gain increasing legitimacy, for instance through grants and scientific outputs.
Collaboration with local organizations and communities: while research centers and higher institutions advocate for the technology itself and the benefit it provides at a broader level, partnering with local organizations like NGOs and community leaders can help gain insights into community concerns and use their networks to facilitate communication.
While these are just general comments that I have been able to observe throughout my research, the energy sector remains a highly debated sector, undergoing major changes. Thus, there is a lot more to it than communication and engagement, and preparing the field to build an ecosystem infrastructure around a green transition can be very complex. With the most promising efforts, projects can still fail. Factual information may provide the technical arguments that speak for the plant, but effective stakeholder engagement fosters trust, cooperation, and shared value among different participants and could help create a supportive environment for problem-solving and innovation.
It seems yesterday that I have started my PhD but, when this blog will be out, I will have already completed the first half. To celebrate this milestone (or to convince myself that has been a fruitful journey), I decided to list one thing per month that I have learnt or discovered. Without further ado, we can start with the first nine:
Learning is not a linear process
Despite this maybe being common sense for someone (or just my personal opinion for someone else), these months have clearly reminded me that to master a topic, two things are necessary: focused and extended practice.
First, I need to focus on a single project at a time. This means that multitasking or working on too many different tasks does not allow you (or, at least, me) to get over that wall you face when approaching a new topic. Second, I need to be consistent for an extended period of time (at least a few days of full concentration before gradually introducing other aspects/subjects). This prolonged practice involves not just reading, but also writing.
These principles resemble what is also known as the S-learning curve (see image below). This is a rather established concept in different fields, which I believe describes well my learning experience.
So, what I wanted to highlight in this blog is its main implication, i. e., the importance of not giving up when at first learning a new subject seems to be particularly difficult. Because, actually, this is how it is expected to be.
Learning is not just about how much you read, but how deep you go Regardless of the topic of your research, just few articles can be defined as foundational. All the rest concerns more marginal aspects of that theory or phenomenon. This means that you don’t need to dedicate the same amount of time to every paper. Just focus on identifying and reading the most relevant articles in your area of interest and this will be enough to set the ground for your research.
However, these articles deserve a deeper reading to really grasp and internalize their contributions.
Thinking (and writing) can be divided into different layers
While I was acting as a censor during a session of oral examinations, the professor I was supporting made me reflect on the way students were expressing their thoughts. The way he was evaluating them was well structured and made me notice that you could not expect a student to get the highest marks (and thus express more elaborated answers) if s/he had not implicitly answered to some basic questions.
The table below exemplifies the questions characterizing the four levels of thinking/writing that he was following to assess the students: descriptive, analytical, critical and reflective.
What is the implication here? In my opinion, if we don’t have clear answers to the first questions, we cannot expect to reach the most advanced levels of thinking and writing on the topic we are studying.
After reading hundreds of articles and starting to write a couple of them, nothing is clearer to me than that good research takes time. And, for now, I am just referring to the planning and writing phase. This means that to identify the right research area, select the adequate case study, refine the research questions, collect data, analyse the findings and generate some valuable contributions might take years.
There is a reason why PhDs in Management in the US (and few other Countries) last for around 6 years, including two years fully dedicated to theoretical courses.
Nevertheless, the path does not end there. As the graph below shows, the review process is not free of hurdles, either. On average, this process takes almost 300 days in the area of management of technology and innovation. Everyone is free to draw their own conclusions here…
The slowest peer review process in any scholarly field is organisational behaviour and human resource management. The average peer review process takes over 322 days. The process takes 94 days in structural biology. https://t.co/c7FiZhQK46pic.twitter.com/efZElXCXtK
In addition to all the previous steps, publishing a paper requires a thorough choice of the right framing for your research. This decision usually concerns:
what journal you are targeting;
choosing whether your paper should be theory or phenomenon-driven;
what theoretical lens is the most suitable to analyse your findings;
how to manage all the activities you are working on in parallel.
For this reason, you should consider at the outset in which journals the conversation you want to contribute is taking place, to avoid wasting time rephrasing the article accordingly at the end.
6. Writing is not an easy task (for anyone)
Some takeaways from my experience:
To write, I need to have read what has been written before on that topic. Even though it might seem a trivial observation (and a boring activity), I believe that perfecting this exercise and taking your time to study the literature is a necessary step that can help avoid problems toward the end of the PhD;
When I read, I try to always have a general goal or direction in mind. However, these goals should not be set in stone, as you should keep refining the research objective and research gaps after every read paper;
Once I am ready to write the first section of a paper, having a structure in mind (reflected on the Word file) of what I would like to focus on makes my writing process more effective;
Always prioritize Freewriting (a technique in which you write down your thoughts without worrying about form or even grammar) and then, in the following waves, focus on adjusting and perfecting the style;
Another tip for improving (or forcing me) to write is joining a Writing Club. Writing Clubs are (virtual or hybrid) meeting where you can briefly talk about your writing goals and progress, writing together with your supervisor or other peers for a couple of hours.
Writing is even harder, especially if you are a non-native English speaker.
During my stay at UC Berkeley I have attended a seminar called “How to Get Published in International Journals”, where the following provocative question posed by the lecturer caught my attention “If a native speaker has to rewrite a paragraph 10 times before arriving at the final version, how many times should you rewrite it?”
Writing in academic English follows rules that are mostly unfamiliar to researchers foreign to the Anglo-Saxon educational system. Therefore, proofreading services are necessary to decrease the likelihood that your research will be rejected because it does not meet the quality standards of a journal. If you want to know more about this topic, this book resumes the five essential strategies for maximizing your publication chances:
Analyzing journals both for elimination and for submission
Organizing and arguing in Aristotelian logic
Editing for strength (less is more)
Editing for clarity
Revising rigorously for language, clarity, argumentation, punctuation, etc.
The importance of planning and organizing your work
As said before, a PhD is a long and winding path where there is always the risk to lose motivation, self-confidence and your final goal.
Notion and OneNote represent two easy but very powerful management tools that have been helping me to keep track of my progress over the years.
Another useful resource is the YouTube channel below.
9. The importance of finding distractions outside academia
Being a PhD should be part of your life and not vice-versa (even if sometimes it is difficult to see the big picture while you are immersed).
This is an advice that I have received multiple times. So, after a first year of PhD full-immersion, I decided to dedicate more time to one of my main passions: running. The result is that in March 2023 I completed my first half-marathon!
Oakland Half-marathon medal Source: photo taken by myself
Robots working alongside humans is becoming more and more probable as robotics technology develops. But when people and robots collaborate, safety is still a major issue. Vision and proximity devices can be used in this situation to guarantee secure human-robot interaction. Robots can detect people, objects, and obstacles in their environment due to vision sensors. They track and identify motion and shapes using cameras and other tools. Robots are able to identify and steer clear of humans and other objects with the help of this ability.
As the use of robots spreads across a variety of sectors, safety concerns regarding human-robot collaboration have taken on greater significance.
Robots can sense their surroundings and identify objects, people, and obstacles with the help of vision sensors.
Proximity sensors can help avoid collisions by detecting the existence of an object or person and their proximity to the robot.
By utilizing both kinds of sensors, robots can more accurately perceive their surroundings and decide how to interact with people.
Human-robot collaboration is becoming more prevalent in the industrial and healthcare sectors, but safety is still of utmost importance in these environments.
While sensors can significantly increase safety, human supervision and training are still necessary to guarantee secure and productive human-robot interaction.
On the contrary, proximity sensors can both sense the presence of an object or person and their proximity to the robot. They employ a variety of technologies, including ultrasonic, capacitive, and infrared sensors, to identify changes in the environment and warn the robot to stop or slow down when a person is close. Robots can more accurately sense their surroundings and decide how to interact with people by combining these two kinds of devices. A robot in a manufacturing environment, for instance, could use vision sensors to recognize nearby people and proximity sensors to determine their closeness. The robot may slow down or halt if the person approaches too closely in order to prevent a collision.
Healthcare is a further application where vision and proximity sensors can be used for secure human-robot collaboration. When working with vulnerable patients, safety is of the highest importance. Robots can help medical workers with tasks like lifting and transporting patients. While proximity sensors can warn the robot to halt if the patient approaches too closely, vision sensors can track the patient’s position and movements. Additionally, sensors can be used by robots to track their own motion and recognize when something is wrong. For instance, a robot with a broken arm may be able to sense when it is moving too quickly or in the incorrect direction and stop before it does any damage. While sensors can significantly increase safety in human-robot collaboration, it is essential to remember that they are not infallible. For the collaboration between humans and robots to be secure and productive, human supervision and instruction are still necessary.
Finally, the integration of vision and proximity sensors can significantly improve the security of human-robot interaction in a variety of contexts, from manufacturing to healthcare. The distance between a person and a robot can also be determined using a depth camera, but it is more difficult to attach multiple cameras to the robot’s skin than it is to attach numerous proximity sensors to various regions of the skin in order to calculate the precise distance from various angles and prevent collisions. The project we’re working on also makes use of a camera and a proximity sensor for secure human-robot collaboration.
As part of the program I have the opportunity to go to Finland and visit both my industry partner Jakamo, as well as the LUT university. Now the time has finally come and I have arrived in the lovely city of Tampere, where I will be staying for my first two months. I was lucky to be met not only by great weather, but also the amazing team of Jakamo. During my stay I will conduct research in the field of ecosystem legitimacy, using Jakamo as a case study. At the same time, I will gain important industry insights and can engage with the team here so that we can learn from each other. For now I will focus on settling in, which does not seem too hard with such great company showing me the sights of Tampere 😉
I am thankful for this opportunity and am excited to see where my journey here takes me. While working with Jakamo, I will also post on their blog on supplier experience, so stay tuned for more to come!
Approaching Tampere. Picture by Finn TryggvasonTampere Town Square. Picture by Finn Tryggvason
After work sunbathing with the team. Picture by Timo Rossi
Pitfalls and Blessings: A 21st century Research Journey
Being in the academic world these days comes with many pros and cons, ups and downs, privileges, and struggles. On average, doctorate holders represent 1.1% of the 25–64-year-old population across OECD countries (source). That sounds like a very small percentage. But let us put this number a little bit into perspective: In 2006, approximately 1.3 million peer-reviewed scientific articles were published, synonymously leading to a rise in scientific journals from 16.000 in 2001 to more than 23.000 in just five years (source). Today the number of available journals to choose from is even larger, a presumed 30.000+ while, at the same time, enabling lower quality journals (source). You might think “paradox of choice”, how to decide which journal to go for?
Unsplash picture by Claudio Schwarz
Let us add another lens to that: “Fewer than 1%—manage to publish a paper every year” (source). Publication practices have long received the slogan: “publish or perish” (that speaks for itself) across disciplines such as medicine (source) and management studies (source). Assuming you have made it into a journal, about one third of articles in the social sciences do not get cited, much less in the natural sciences, but even more in the humanities with an approximate 80% of publications never getting cited after publication (source).
Publishing in a scientific journal has become a significant challenge. A challenge so significant that a professor once said to me, “When you receive the response from a journal inviting you to revise your manuscript – you celebrate” (Note, this does not mean the paper has been accepted yet, but it has moved on to round 2). A study on journal acceptance rates at Elsevier found an average of 32% of papers that make it past review (source) while “scientists suffer constant pressure to publish new work frequently” (source). In the case of a paper-based PhD, it is often mandatory to get papers into the review process while working on the PhD. Fortunately, actually being published by the end of the PhD is not necessarily a requirement – although it certainly will not hurt. But looking at the statistics sheds a light on the chances of doing that.
The lifecycle of scientific publishing only works with the valuable and dedicated time of unpaid reviewers but the pressure in the academic world is high, and an elbow-mentality is growing. In recent years the peer-review process is receiving some significant backlash. An article published by the highly recognized Journal of Management Studies almost read like a long-suppressed outcry: “Reining in Reviewer Two: How to Uphold Epistemic Respect in Academia”, criticizing the behavior of a reviewer who deprecated the use of low-tier journals (source). In a similar vein, DORA (the Declaration on Research Assessment) was formed in 2012 in order to improve ways in which researchers and research outputs are evaluated (source) and to date, more than 20,000 individuals and organizations have joined in, promoting this objective. While epistemic respect is crucial for scientific publishing, criticism and accepting rejection is the “daily bread” as Germans would say, or “the norm” for every researcher. However, a rejection by one reviewer or one journal does not decrease the value of the manuscript. Publishing is a journey and taking it from an Associate Professor at Princeton: “Authors should be wary of being drawn into this morass until they find an interested editor“ (source). And, I too know researchers who publish more than one paper a year—nothing is impossible.
Unsplash picture by Nathan Dumlao
It goes without saying that we have achieved a few milestones in education and academia in general. Higher education enrolment rates have almost doubled to close to 40% worldwide since the beginning of this century to 2018 (source). Education has become increasingly accessible to people around the world and this is a great achievement in many ways. However, there is no such thing as a flawless education system and scientific publishing has become an obstacle like never before. But along the ups and downs and the long way ahead, being able to learn, publish, and contribute to knowledge generation, informing others about our findings feels so very rewarding at the end of the day. Being able to produce research and working on the world’s challenges and concerns, in my humble opinion, is still worth the hours we put into it.
“Any fool can know. The point is to understand.”
― Albert Einstein
“The best way to predict the future is to invent it.” – Alan Kay
Hello everyone! I’m happy to share some experiences that I’ve made during the last month. Recently, I had the incredible opportunity to accomplish my academic secondment at Aarhus University in Denmark and attend the European Robotics Forum in Odense with my EINST4INE colleague Alejandra Rojas.
ERF23
The European Robotics Forum (ERF) is an annual event that brings together experts in robotics from industry, academia, and government to discuss the latest developments in the field and explore potential collaborations. The forum is organized by the European Robotics Association (ERA) and typically features keynote speeches, technical sessions, panel discussions, and exhibitions showcasing the latest robotics technologies and applications.
The ERF serves as a platform for researchers, engineers, and entrepreneurs to exchange ideas and knowledge on a wide range of topics related to robotics, including industrial automation, healthcare robotics, service robotics, and artificial intelligence. It is also a forum for policy makers and industry leaders to discuss the challenges and opportunities presented by the rapidly evolving field of robotics, such as ethical and legal considerations, workforce training, and investment strategies. Even Crown Prince Frederick, His Royal Highness of Denmark, attended the event this year!
ERF23 with EINST4INE colleague Alejandra Rojas. Source: own photo.
As a visiting researcher, I was thrilled to be able to connect with so many people who are passionate about robotics and human-robot interaction. I was able to learn about the latest developments in this field. I was particularly interested in discussions surrounding collaborative robots, which are designed to work alongside humans in manufacturing and other industries. During the forum, I had the pleasure of engaging with some brilliant minds, from both the academic and practitioner side. Their contributions to the discussions were invaluable, and I learned a lot from them.
Exploring the Fascinating World of Robotics
In addition to my research on collaborative robots, I’m also fascinated by other robotic technologies such as drones and robotic dogs. These technologies are shaping our world in profound ways, and I believe they have enormous potential to improve our lives. For example, drones have the ability to conduct aerial surveys, deliver packages, and even help with search and rescue missions. Robotic dogs, on the other hand, can be used in a wide range of applications, from military and law enforcement to assisting people with disabilities. I find the intersection between these technologies and human needs to be particularly interesting, as it challenges us to think about how we can design and use robots in ways that are safe, ethical, and beneficial for society as a whole.
Robotic Dog ERF23. Source: own photo.
The Journey Goes On
Aside from the forum, I also spent time at Aarhus University, where I was conducting interviews with SMEs located around Denmark. These interviews are an important part of my research, as I’m studying the implementation of social and collaborative robots in organizations. By understanding the effects of cobots on an individual and firm-level, I hope to achieve a clearer understanding of cobot implementation processes, organizational opportunities and challenges.
Visit at AU with Agnieszka Radziwon and Cristina Marullo. Source: own photo.
Overall, my trip to Denmark was an amazing experience, and I’m so grateful for the opportunity to connect with so many brilliant minds in the robotics field. I’m excited to continue my research and see what developments the future holds for human-machine interaction models. I am also looking forward to the next EINST4INE Summer school and see my ESR friends in person again. Thanks for reading!
On March 9th, 2023, I attended a masterclass on “Purposeful Curiosity”, hosted by the ESADE business school in Barcelona and held by Professor Constantine Andropoulos. The theme of the event was curiosity and how best to manage this resource.
The picture was taken by Chiara Mariottini
In our daily lives, we are continuously overwhelmed by a huge load of data through social media, texts, e-mail, and streaming services that distract us from focusing on deeper understanding and knowledge. Nonetheless, when we take the time to refine our interests and skills, curiosity – if harnessed purposefully – can take us to unexpected places and provide us with new paths to fulfillment and success.
Professor Constantine Andropolous collected interview data from hyper-curious people – including Formula One engineers, scientists working to grow food on Mars, polar explorers, athletes, and star chefs, ending up being able to explain how the most capable people overcome the ‘noise’ of information overload and use the productive power of curiosity to discover, create and succeed.
During the meeting, the professor introduced the concept of “frivolous curiosity”, distinguishing it from the idea of purposeful curiosity aimed at exploring specific topics. According to existing literature, curiosity helps us survive, leads to higher achievement (Von Stumm et al., 2011), makes us happier (Kashdan et al., 2010), can expand our empathy (Gino, 2018), makes us come across warmer and more attractive (Kashdan and Roberts, 2005) and is associated with longevity (Swan and Carmelli, 1996).
The picture was taken by Chiara Mariottini
A Q&A session then took place during the meeting, from which much food for thought emerged on how to invest our time in something that really interests us and how best to focus our attention on targeted interests that can really help us expand our knowledge and perspectives. This is particularly relevant in the research and PhD pathway, where we may encounter different inputs and stimuli. The challenge lies in identifying the topics that most interest us and then exploring them properly, hence purposeful curiosity can be a valuable support.
During my current academic placement with RMIT in Melbourne, Australia I have the chance to network with colleagues from the School of Business, attend talks and seminars and collaborate with other departments and researchers from different fields!
One example is the summer school led by the Digital Ethnography Research Centre (DERC) [https://digital-ethnography.com] here at RMIT Melbourne which I attended at the end of February. During the summer school Early Career Researchers (mostly PhDs) from all over the world got together to learn from Annette Markham and Larissa Hjorth about “Digital Ethnography Fieldwork and Analysis: Studying hybrid contexts of human+ non-human+ more-than-human entanglements”.
What is Digital Ethnography?
Slide from the summer school (Source: picture taken by C. Leeb).
Digital ethnography encompasses a lot of things. In general, it means investigating how digital technology impacts humans and society by using ethnographic tools. For example, how people use and interact in the digital space (e.g., on social media platforms like Instagram or Twitter, online forums, games, etc.) and trying to understand how this impacts the end-user. Just like the EINST4INE researchers, digital ethnographers investigate digital transformation. They are taking a very human-centred approach to this and are interested in the lived experience and feelings of the people using digital tools. I was lucky enough to be able to participate in this summer school, and I can only say: What an amazing summer school and what a great fit to my research!
The Summer School
The summer school lasted a week, plus an extra day for PhDs to present their work.
We heard lectures on various topics, such as how to do ethical research or on important themes in fieldwork (e.g., immersion, continuous documentation, using “what’s at hand” to generate material). Further, a penal discussion of former PhD students doing Digital Ethnography gave us insights about the possibilities in this research area. We heard from Marissa Willcox (University of Amsterdam), Zöe Glatt (London School of Economics), Kelly Chan (RMIT University) and Jess Hardley (RMIT University). We also had workshops in which we did our first ethnographic fieldwork, we learned how to write field notes and how to use video and photos to document our experiences.
Halfway through the summer school, we did one day of fieldwork out in the public space. We were divided into 6 groups. Half of the groups observed the interactions inside the Australian Centre for the Moving Image (ACMI) and the other half on Federation Square in Melbourne. But – this was not all!
We actually observed something very specific, as we had another participant joining us: Boston Dynamic’s robot Spot!
Spot on Federation Square (Source: picture credits to Alison Starr).
The focus of our observation and field day was to see how people of the public react and interact with Spot. This day was very insightful and lots of fun!
After that, we started reflecting on our experiences as a group and heard lectures on some useful tools for the analytical processing of the data, namely on Situational Mapping and Critical Making techniques. Then, each group put together two presentations to share with the other participants: one on our initial reflections of the field day and one on initial findings from the first attempts of analysing some data.
Personal key take-aways
I will very shortly touch upon 3 key take-aways from this summer school:
Ethical considerations: Before, during, and after doing research.
It was great to discuss this central topic in research again: how important it is for a researcher to constantly reflect on ethical considerations.
Before the research this seems obvious to most: often simply because you need to obtain ethical approval to do your study. But it doesn’t end there, continuously throughout your data collection time – you need to be aware of your positionality (am I an outsider, an insider?), what effect your research or your presence in the field could have on others, and that you will always bring in subjectivity when entering a field. The more you reflect on these things, the better and the more you can ensure that your research will be ethical. Ethics is not simply an approval to obtain – it is there to support you to do the right thing. It helps you to reflect on possible issues that might arise and to plan ahead on how you will react to them.
Looking at the data in a group: Surprises can emerge.
During the analysis stage, we had access to the data we collected ourselves and the data from all other researchers. A key take-away for me here is that looking at data in a group can lead to many different insights and surprising themes! It enriches the analysis process greatly as every member brings a unique point of view into the discussion.
It was exciting to see all the interesting themes that emerged during the analysis process with my group. We talked about the agency of oneself and how we ascribe agency to others (e.g., Spot). While I wasn’t too surprised that participants seemed to struggle to categorize Spot (Is it a dog? A horse? A spider?), I was intrigued by the fact that most people really wanted to categorize it. They either asked a lot of questions or started treating it in a certain way (e.g., petting it etc). Other interesting topics that emerged were control (people started giving Spot commands) and embodiment (participants reflected on their feelings in a bodily sensation).
About half of the participants of the summer school + Spot at Federation Square. (Picture credits to Haryo Jiwandono).
Not just valuable learnings: Good company & good food.
The last key take-away is clearly that I learned a lot and enjoyed the summer school greatly. I met fascinating people from all (literally every continent except Antarctica was represented) over the world from various disciplines (architecture, urban studies, anthropology, design, journalism, organisational studies…). Actually – one of them, Kateryna Kryzhanivska, who is also a visiting PhD researcher at RMIT, and she is from LUT University, Business School! (which shows again that the world can be really small as well).
Who knows – maybe some of these connections will last and result in future collaborations!
Further, good food is a great plus in any event.
The desert at the Welcome Dinner provided by “Piecurious” run by Helen Addison-Smith (picture taken by Constanze Leeb).
All in all I can say:
It was intense, insightful and amazing – a week well spent!
Completing a PhD is an intensive and demanding task. As a PhD student, we spend countless hours scouring through academic literature, collecting data, analysing information, etc.. The good news is that advanced technologies, such as ChatGPT, can help make this process much easier.
ChatGPT is an artificial intelligence (AI) chatbot developed by OpenAI designed to understand and generate human-like language. The advantage of ChatGPT is that it can help make the process of searching and analysing online information much faster.
Here are some ways ChatGPT can help PhD students do research:
Finding relevant literature
One of the most time-consuming tasks for PhD students is finding relevant literature for their research. ChatGPT can help by providing instant access to a vast collection of academic literature. With the help of natural language processing (NLP), ChatGPT can quickly search and retrieve relevant papers, books, and other academic sources, saving you valuable time and effort.
Generating research questions
ChatGPT can also help PhD students brainstorm research questions. By inputting keywords or phrases related to your research topic, ChatGPT can generate a list of potential research questions. This can be especially helpful when you’re stuck and need some inspiration to jump-start your research.
Data analysis
Data analysis is an essential aspect of many research projects. ChatGPT can be used to help with this by assisting in the analysis of complex data sets. With its NLP capabilities, ChatGPT can quickly identify patterns, trends, and correlations in data, providing valuable insights that can help support your research conclusions.
Writing assistance
Another critical aspect of the research process is writing. ChatGPT can help PhD students with their writing by providing suggestions for grammar, style, and tone. It can also generate summaries, abstracts, and even full paragraphs, which can be useful when you’re struggling to articulate your ideas.
Literature reviews
ChatGPT can be used to assist with writing literature reviews. It can help to summarize key findings and highlight important points from multiple sources, making the process of synthesizing and analysing academic literature much more manageable.
Of course, ChatGPT does not work miracles and should also not be trusted blindly. PhD students need to be attentive to potential biases, as an example. They will also need to make sure that the answers provided by ChatGPT are used as a brainstorming or supporting tool, and not as something that limits their thinking. Yet, as we move to a world increasingly dominated by advanced technologies such as AI, we would benefit from thinking about how we can use it to advance our work, making us more efficient and effective researchers.
In short, ChatGPT can be an incredibly valuable tool for PhD students, helping to streamline the research process and save time and effort.
During my PhD studies in the third semester, I had the opportunity to assist and teach some classes about the digital economy and specifically about digital platforms and ecosystems. While I hope that the students learnt as much as I did, I became highly interested in one topic:
Digital Industrial Platforms
Before diving into what digital industrial platforms are, it seems useful to define what digital platforms are:
Dating back to the nineties with the onset of the Internet and the increased communication and creation of online communities, native digital platforms such as eBay started to emerge, facilitating online commerce. Later, Amazon and Google made the most of the power of the network to become what they are today.
Nowadays, as technology continues to advance and pierces through new industry boundaries, new types of platforms have emerged. Industry 4.0 and the Internet of Things have led to the emergence of digital industrial platforms which allow firms to connect and collect data from industrial machinery and their environment in order to co-create new solutions and services.
GE’s Predix is one example of a digital industrial platform.
Check out GE’s “Predix” platform:
But, unlike commercial platforms, digital industrial platforms serve as both innovation and transaction platforms. They collect and analyze data from different industrial assets and make this information available to third-party companies so that they can create complementary products and services. Many of these platforms also act as a marketplace where they sell these solutions to industrial customers.
Another difference between B2C and B2B platforms relates to the way they are “built”. The rules that apply in the B2B sector may not apply to the B2C, as network effects are not as prevalent in the manufacturing industry due to the more complex nature of industrial products and the relationships between the third-party developers as well as the customers and the sellers.
What we can say, is that all digital platforms have a technological basis. Industrial platforms are an interesting case as they converge different types of machinery, digital, enabling, and general-purpose technologies. A recent paper by Jovanovic et al. (2022) assessing the creation of different industrial platforms illustrates the evolution of the connection between these technologies:
Most platforms start with collecting data about each machine or product through the installation of sensors. With this, companies gain a better understanding of their machinery and the connected processes.
Through analytics, the use of “advanced” sensors can give more information about the performance and weaknesses of the machines. With this, they are able to gather huge amounts of data that they store in a cloud (e.g. Microsoft Azure, AWS, etc.). This helps companies to proactively discover anomalies, and react before a problem arises.
Finally, AI technologies can help assess the technicalities and data generated by machines and their surroundings. Most importantly AI technologies contribute to the autonomy of the system, like the GE Predix platform, where trains can accelerate and decelerate depending on if you’re driving up a hill or down a hill.
So, even though most scholars have agreed that technology can drive the growth of ecosystems, we still don’t know much about the interaction of these technologies and how they are connected to the formation and expansion of ecosystems. .. So stay tuned while we find out!
References:
Jovanovic, M., Sjödin, D., & Parida, V. (2022). Co-evolution of platform architecture, platform services, and platform governance: Expanding the platform value of industrial digital platforms. Technovation, 118, 102218. https://doi.org/10.1016/j.technovation.2020.102218
In 2019 at the preview for Art Basel Miami Beach a banana taped to the wall (Figure 1) was sold as a piece of art at the cool price of 120.000 dollars. Subsequent versions from the same artist saw an increase in their price [1]. In August 2022, Jason M. Allen won the first prize (300 dollars) at a Fine Arts Competition in Colorado by submitting a digital image (Figure 2) [2]. Both recent art episodes provoked turmoil. The first, for obvious reasons. The second, because the winning image was generated entirely by an artificial intelligence (AI) program.
The debate around what’s art and what’s not has puzzled numerous cultures and societies. Far from being solved, the appearance of the ‘AI artist’ in the scene has already rocked the boat.
Figure 1: Maurizio Cattelan’s Comedian, for sale from Perrotin at Art Basel Miami Beach. Source: Sarah Cascone [1].Figure 2*: Jason M. Allen’s piece “Théâtre D’opéra Spatial” which he created with AI image generator Midjourney. Source: Rachel Metz [2].In recent years, artificial intelligence (AI) has made significant strides in its ability to generate content, including images, text, and video. This development has the potential to revolutionize a wide range of industries and has already begun to have a significant impact on fields such as media, advertising, and entertainment.
One of the most impressive examples of AI-generated content is the development of machine learning algorithms that can create realistic images and videos. These algorithms, known as generative adversarial networks (GANs), work by training a machine learning model on a large dataset of images or videos. The model then uses this training to generate new content that is similar to the examples in the dataset.
Figure 3*. Source: Ido Beeri [6].The results of these AI-generated images and videos can be truly impressive. In many cases, it is difficult to distinguish AI-generated content from real images or videos. This has led to the use of AI-generated content in a variety of applications, including the creation of virtual reality environments, the development of video game graphics, and the creation of advertising materials.
AI is also being used to generate text content, such as news articles and social media posts. In some cases, these AI-generated texts are indistinguishable from those written by humans. This has led to concerns about the potential for AI to replace human writers and journalists in the future. However, it is also worth noting that AI-generated text has the potential to assist human writers in the creative process and to enhance the efficiency of certain tasks, such as data analysis and research.
Figure 4*. Source: Keith Burgess [7].While the use of AI to generate content has many potential benefits, it also raises a number of ethical and societal concerns. One concern is the potential for AI to be used to create fake or misleading content. For example, AI-generated images or videos could be used to create fake news or to manipulate public opinion. There is also the risk that AI-generated content could be used to exploit vulnerable populations, such as by creating targeted advertising that preys on people’s insecurities or by creating fake social media profiles to spread misinformation.
In light of these concerns, it is important that the development and use of AI-generated content be carefully regulated and monitored. This may require the development of new ethical guidelines and the creation of oversight bodies to ensure that AI is used responsibly and ethically.
Overall, the ability of AI to generate content is an impressive and potentially transformative development. However, it is important to approach this technology with caution and to consider the potential risks and ethical implications of its use. By carefully managing the development and use of AI-generated content, we can ensure that it is used for the benefit of society and not to the detriment of individuals or groups.
Figure 5*. Source: James Gill [8].
The above paragraphs in italics have been generated by an AI algorithm, called ChatGPT [3], from an input of a few words:
‘Write a 700 words essay about AI now being able to generate content (e.g., images, text, video).”
The information written in those paragraphs has not been fact-checked, therefore could be inaccurate. Whereas the images marked with an asterisk have been generated by another AI, DALL-E 2 [4], always from a text string.
Having tried the AI to generate content for this and other exercises, the best summary of what AI like ChatGPT constitutes is: “a plausible idiot” [5]:
“It gets just enough right, saying just enough words, to sound plausible and authoritative to anyone who doesn’t know the subject matter well. But it also gets enough wrong that you cannot rely on its accuracy, and if it is talking about a subject you know well it is sometimes laughable how wrong it is.”
Clearly, this technology is not able to entirely replace human creativity (yet). Surely, AI has the potential to support and complement the work of humans by providing them with new tools and resources to create content at an unprecedented speed and ease. Humans bring a unique and valuable perspective that cannot be replicated, however AI has already changed the industry of content creation as we used to know it.
[1] Cascone (2019). Maurizio Cattelan Is Taping Bananas to a Wall at Art Basel Miami Beach and Selling Them for $120,000 Each. https://news.artnet.com/market/maurizio-cattelan-banana-art-basel-miami-beach-1722516. Accessed on 17/12/2022.
[2] Metz (2022). AI won an art contest, and artists are furious. https://edition.cnn.com/2022/09/03/tech/ai-art-fair-winner-controversy/index.html. Accessed on 17/12/2022.
[3] codingdave. https://news.ycombinator.com/item?id=33863563. Accessed on 17/12/2022.
[4] https://chat.openai.com/chat. Accessed on 17/12/2022.
[5] https://openai.com/dall-e-2/. Accessed on 17/12/2022.
[6] Ido Beeri. Generated using DALL-E 2 from the prompt: “A children’s book with beautiful elephant trunks made of hyperrealistic impossible tesseracts, about the boy who wanted to be a cauliflower. Written by Joan of Arc and Illustrated by Albert Einstein himself. In shades of red, embossed in papers made of iron. Extremely detailed photography with all elements, f/1.8.” https://www.facebook.com/photo?fbid=5749060345181941&set=pcb.686953656332661. Accessed on 17/12/2022.
[7] Keith Burgess. Generated using DALL-E 2 from the prompt: “Salticidae Celebrating Saturnalia.” https://www.facebook.com/groups/dalle2.art/permalink/684302463264447/. Accessed on 17/12/2022.
[8] James Gill. Generated using DALL-E 2 from the prompt: “Superman saves Christmas, painted by William-Adolphe Bouguereau.” https://www.facebook.com/photo.php?fbid=10159273294882333&set=p.10159273294882333&type=3. Accessed on 17/12/2022.
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