Copyright and AI

Liesl Rowe – Snr Digital Library Advisor (Copyright), Leeds Beckett University

Like many people in the Higher Education sector, I’ve been watching Artificial Intelligence develop with interest and concern. AI can help significantly with the research process, but new complications come alongside those benefits. Some of the less talked about issues are copyright related: we need to consider what we choose to input into AI as well as the output. 

‘Assume that any material which remains in copyright cannot be added to an AI dataset’

It’s important to remember that when inputting information into a chatbot, that data can often be used to “train” the AI. ChatGPT explicitly states that one of the three main sources for the language model is information provided by human trainers or users. At the moment under UK copyright law, copyrighted material inputted into an AI dataset would count as a “copy” being made of that work and be in breach of copyright law. The recent government consultations on AI have talked about changing this, so data mining will be permitted to harvest copyright protected content. However, this is not presently codified in law as an exception.

As such, we need to continue under the assumption that any material which remains in copyright cannot be added to an AI dataset. To take an example, you could ask the AI to summarise a piece of text for you. Depending on if the text was covered under copyright, inputting that could be an issue under copyright. 

So when inputting data into an AI, make sure it’s not copyrighted data. That includes data that you intend to exist within copyright: if you’re publishing a journal article and input the data into an AI bot, that would count as a copy. For instance, one standard prompt engineering technique is using the AI to analyse a piece of writing. If you were to use the AI to analyse a piece of your writing, then seek publication in a journal, the publishers might consider copies stored within an AI training set as going against any embargoes they have in place.  

Sensitive & personal data

You also need to consider if any data you’re inputting into the AI is sensitive or personal. This was an issue recently in Italy where ChatGPT was temporarily suspended as the Italian government felt that the AI training data was making use of personal data which its users hadn’t fully knowingly agreed to share.

To take a more university-focused example, inputting the results of a research study into an AI might allow us to process the data more quickly and look for trends…but we also have no control over where that data goes after we’re finished using the AI.  

Hallucinating…

On a completely different tack, AI can also create data out of nowhere: this is known as “hallucinating”. So it can recommend journal articles or books which don’t exist; espouse an academic’s views or a quotation which were never said. As a result, it’s worth never relying on an AI for reliable facts. It’s better to consider it a starting point for research. 

So what can we do about this as researchers who want to take advantage of the new technology? I don’t think stopping using AI is an option. Like it or not, this technology is here to stay and has some fantastic capabilities which can help us. We just have to think carefully about what uses we’re putting AI to and what happens to any data we choose to share. 

A few top tips:

• First, always read the Terms and Conditions of the AI software you’re using. It will give you a clearer idea of what the AI is doing with your data and any privacy implications for your work. 

• Second, it’s best to work on the assumption that any data is being stored as part of their training base and act accordingly. Don’t input sensitive data. Check publishers’ views on AI having had access to a version of your manuscript.  

• Thirdly, when using AI for research purposes, make sure you cross-check any data it inputs out to make sure it’s correct and not a “hallucination” from its dataset. 

• Finally, if you’re unsure, don’t be afraid to use your library for advice! AI is a rapidly changing field and we want to help you keep abreast of any changes which will impact your work.

Review of free digital tools for inclusive recruitment

Rowan Williamson University of the Arts

Inclusive recruitment is a high priority for many libraries right now. Not only does it fit into our values, there are imperatives around creating a diverse workforce for many organisations. CILIP’s workforce data in 2015 highlighted that 97% of the library workforce is white. The latest survey data from 2022 was published this week, showing there is little movement in those figures. It’s proving a tricky statistic to change, often perceived as a ‘pipeline’ issue in the profession, especially with declining levels of new professionals coming in, and such a lack of diversity in the existing workforce. So attracting a diverse workforce into new roles and into the wider profession is a challenge for us all. There are many ways to tackle this, re-evaluating our qualifications requirements, introducing apprenticeships, and updating job descriptions being among them.

There are many new recruitment solutions coming on the market offering to address the concern about how we articulate our requirements for prospective employees. But not everyone has access to the recruitment packages that large companies have resources to subscribe to, so we took a look at some of the free digital tools available at the moment, and discussed how they can help us with our inclusive recruitment practices.

Gender bias tools

This is an interesting one. At first glance we assumed that ‘bias’ is a bad thing and maybe we should be aiming for a neutral score. However having tried a few of these tools now it has become apparent that they are an interesting conversation starter about the language you use, but not necessarily something that you should apply in this way.

For starters it is worth reading how the free tools work. The ones we used are based on a word list, which simply divides into masculine coded and feminine coded words. https://gender-decoder.katmatfield.com/about, is based on a research paper written by Danielle Gaucher, Justin Friesen, and Aaron C. Kay back in 2011, called Evidence That Gendered Wording in Job Advertisements Exists and Sustains Gender Inequality (Journal of Personality and Social Psychology, July 2011, Vol 101(1), p109-28).

You can, and should, look at the word list! It does of course reflect stereotypical gender coding, and it does not touch on non-binary people. And this is a little problematic.

For one thing, we are essentially a support service, and the word support is feminine coded and comes up a lot. Does this account for the dominance of women in Library work? Even more fascinating; words like ‘lead’, ‘leadership’ etc are masculine coded. So our job descriptions got less feminine biased as they moved up the pay scale. But don’t get too excited because we tried this out on other departments job descriptions too, and even our IT jobs which we know are predominantly attracting men, came out with feminine bias. The Total jobs decoder includes some really interesting statistics from their own analysis which looks at the difference in sectors and job levels. https://www.totaljobs.com/insidejob/gender-bias-decoder/

Interestingly what we discovered when we tried this tool on a range of our job descriptions, was that ALL our institutions job descriptions seem to be feminine coded. Looking at our institutional values and the language we use, reflecting on the list, this is maybe unsurprising. But of course we then have to ask, if this is the language we are using and it aligns with our values, do we want to change that? And then there is the fact that according to the research this tool is based on, women felt that job adverts with masculine-coded language were less appealing and that they belonged less in those occupations, but for men, feminine-coded adverts were only slightly less appealing and there was no effect on how much the men felt they belonged in those roles.

So overall we were happy with what the tool showed us. Even our more senior posts came out as feminine coded. Had they not, would we worry? I am not sure that this tool is complex enough to base a re write on, but it was interesting to consider.

Ethnic and cultural language

Casey by Croud Casey is named after the feminist author and advocate of non-sexist language, Casey Miller. Casey is designed to catch potentially offensive language choices, such as gender favoring, polarising, race-related, religion-inconsiderate, or other unequal phrasing. Even giving this a lot of thought, my own perspective and knowledge were not enough and it managed to flag up instances of language that could be profane in some contexts . Of course the example it found seemed so unlikely to be interpreted this way it was not really a cause for concern (‘laid’!) But good to know that we didn’t have any other examples!

Social theory and language

Going beyond the idea of masculine and feminine coded language, you could take a deep dive into the ideas and work of Darren Flynn (University of Northampton) on social class, using social theory to develop a framework of coding language according to attributes and behaviours being described in job descriptions. Darren has recently presented his findings from a research study exploring potential social class bias in recruitment to teaching librarian roles at LILAC. He describes how in his research he took person specification criteria and ‘coded them using a four-part framework based on social psychological research to identify if criteria were weighted towards social behaviours and attitudes associated with working or middle class predispositions and values’. Though this is a massive and complex piece of research into the attributes we might be looking for in these roles, it also provides insights into how certain language describing our roles might create social bias. There isn’t a digital tool for checking this as yet, but we can see lots of potential for developing a coding tool around social theory and frameworks such as these!

Plain English

The Hemmingway Editor was very valuable as it not only showed up sentence structure, but language and phrasing. We managed to create something much more accessible using this, although it did generate another interesting discussion around the appropriate level of language. Some alternative wording that it offered was not really suitable for us, and we were careful to keep in mind that readable language does not have to be dumbed down vocabulary, as long as it is appropriate to the level of job you are advertising. Some of these tools like the Jobvite job description grader are better at offering a ‘readability score’ which informs you if it grades you as ‘post college’ level for example. It also uses sentiment analysis and scores you according to how positively your role comes across compared to others!

Embedding good practice in your writing

All these tools are really helpful and very usable as you basically just select the text you want and paste it into a box to view instant results. But to embed this sort of checking as you work you can also use Microsoft Words inclusive language tools in the editor settings. These are available in the Office 365 version and are turned off by default, but can be switched on by selecting from the Editor grammar settings.

More free tools for you to check out are below:

• Idealrole.com
• Gender Decoder
• Eploy
• Applied Text Analysis

Our conclusion, is that these are definitely worth a look, especially as we are seeing our institutions starting to recommend using them. But as with all things, there is no purely technical solution or quick fix for this work. Creating inclusive job descriptions and adverts takes time and effort to balance your needs with careful and considered words. Though bias checking tools can start some great discussions about your process, it is the conversations with colleagues and the shared understanding that develops that is really valuable.

Artificial Intelligence evaluates it’s own performance – Part 4 in our AI on AI series

Followers of our blog may have realised that our latest series of blog posts used ChatGPT to answer a series of questions about the impact of AI on libraries. In our final post of the series we asked it to evaluate it’s own performance in writing these blog posts! This is it’s response.

‘As an AI language model, I strive to generate content that is coherent, informative, and relevant to the given topic. However, it is important to note that there are differences between AI-generated content and content written by humans.

AI-generated content is based on patterns learned from vast amounts of data, while human-generated content is influenced by personal experiences, perspectives, and emotions. Human writers have creativity, intuition, and contextual understanding that AI may not possess. AI-generated content may lack the nuances, tone, and emotional depth that human writers can convey.

On the other hand, AI-generated content can be generated quickly and can provide a wealth of information based on the data it has been trained on. It can also assist in generating content on a wide range of topics. However, it is important to verify the accuracy and reliability of the information generated by AI, as it may not always be perfect.

In the case of a blog post on the impact of AI on libraries, an AI-generated post can provide insights and information based on its training data. However, it is always advisable to have human writers review and edit the content to ensure accuracy, coherence, and relevancy to the target audience.

In conclusion, while AI-generated content can be useful in generating information and insights, it is essential to understand the differences between AI-generated content and human-generated content and use them judiciously in creating high-quality and reliable blog posts. Collaboration between AI and human writers can result in the most effective and impactful content for readers’

The Digital Technology Group has enjoyed ‘interviewing’ our guest blogger AI. Initial observations from our experiment are that it is impressive, and unsurprisingly a lot quicker than us at generating content. But it was a good exercise in understanding a bit about AI and also a bit more about our own blogging. Our stand out observation is that when it comes to the blog, the questions we are addressing and the view point of the blogger matter. Asking the right questions and presenting balanced views are essential. We look forward to publishing comment and content from our colleagues in the library world to continue and even challenge the current debates about AI’s role and impact in the library world as the year progresses!

The DTG committee

AI on the risks of Artificial intelligence in libraries Part 3

Last week we asked Chat GPT about the impact of AI on libraries and got a summary of things AI could be used for. DTG felt this was not a balanced view of the full ‘impact’ so we asked a slightly more direct question about the risks. For this week’s guest blog post by ChatGPT AI, here is what it says…

Artificial Intelligence (AI) has undoubtedly brought transformative changes to libraries, but along with the benefits, there are also potential risks that need to be carefully considered and addressed. As libraries increasingly adopt AI technologies, it is crucial to be aware of the potential risks and challenges they pose to safeguard the future of these vital knowledge repositories. In this blog post, we will explore some of the risks of AI in libraries and discuss ways to mitigate them.

1. Bias and Discrimination in AI Algorithms

AI algorithms are trained on vast amounts of data, and if this data contains biases, the algorithms can inadvertently perpetuate those biases in their outcomes. This can result in biased search results, recommendations, and decision-making, which can have serious implications in libraries. For example, biased AI algorithms may not provide equitable access to information, leading to discrimination against certain user groups, such as marginalised communities or individuals with diverse backgrounds.

Libraries must carefully curate and pre-process the data used to train AI algorithms to minimise biases. This includes ensuring diversity and representativeness in the data used for training. Regular audits of AI systems for bias and discrimination should be conducted, and any biases identified should be addressed promptly. Libraries should also actively involve diverse stakeholders, including users and communities, in the development and testing of AI technologies to ensure that potential biases are detected and mitigated early on.

2. Privacy and Security Concerns

AI technologies in libraries may collect and store vast amounts of user data, including search queries, borrowing history, and user profiles. This raises concerns about privacy and security. Libraries have a responsibility to protect the privacy and confidentiality of user data and ensure that it is not misused or accessed by unauthorised entities. Additionally, there is a risk of data breaches, hacking, and misuse of AI technologies, which can compromise the security and integrity of library systems and resources.

Libraries must implement robust data privacy and security protocols to safeguard user data. This includes encryption of data, regular security audits, and access controls to restrict unauthorized access to AI systems and user data. Libraries should also clearly communicate to users how their data is being collected, stored, and used, and obtain explicit consent for data collection and usage. It is also essential to comply with relevant data protection laws and regulations to ensure that user privacy is respected.

3. Ethical Considerations and Accountability

AI technologies raise ethical considerations, such as transparency, explainability, and accountability. AI algorithms can often be complex and opaque, making it challenging to understand how they arrive at their decisions. This lack of transparency can erode trust in AI systems, and users may not fully understand the limitations, biases, and implications of AI technologies used in libraries. Additionally, there may be concerns about accountability and responsibility when AI systems make decisions or provide recommendations that affect users’ access to information and resources.

Libraries must ensure that AI technologies are transparent and explainable. This includes providing clear explanations of how AI algorithms work, what data they use, and how they arrive at their recommendations or decisions. Libraries should also establish mechanisms for users to provide feedback and raise concerns about the use of AI technologies. It is important to have policies and guidelines in place to govern the ethical use of AI in libraries, and to hold developers, vendors, and users accountable for the outcomes of AI systems.

4. Impact on Employment and Workforce

The adoption of AI technologies in libraries may raise concerns about the impact on employment and the workforce. There may be fears that automation of routine tasks, such as cataloging or customer service, could lead to job losses for library staff. Additionally, there may be concerns about the skills and training required for library staff to effectively use and manage AI technologies.

Blog post by ChatGPT Mar 23 Version. Free Research Preview. ChatGPT may produce inaccurate information about people, places, or facts.

What AI thinks Artificial Intelligence means for Libraries: Part 2 in our AI series

This week our guest blogger is ChatGPT AI. We asked it ‘what will be the impact of AI on libraries?’

Artificial Intelligence (AI) has emerged as a disruptive technology that is reshaping various industries, and libraries are no exception. As society continues to evolve in the digital age, libraries are embracing AI to revolutionise their operations, services, and user experiences. In this blog post, we will explore the impact of AI on libraries and how it is transforming the future of these knowledge repositories.

1. Enhancing Library Operations: Automation and Efficiency

AI is transforming the way libraries operate, making their processes more automated and efficient. For instance, AI-powered chatbots are being used in libraries to provide quick and personalized assistance to users, helping them with catalogue searches, book recommendations, and other enquiries. These chatbots are capable of understanding natural language and can provide responses in real-time, improving user satisfaction and reducing the workload on library staff.

AI is also being used to automate routine tasks such as cataloguing and metadata tagging. With machine learning algorithms, libraries can automatically analyse and classify large volumes of data, such as books, articles, and multimedia resources, making them easily searchable and accessible to users. This automation not only saves time but also ensures accuracy and consistency in cataloguing, leading to improved resource discovery and user experience.

2. Personalising User Experiences: Customised Services

AI is enabling libraries to provide personalised services to their users. By analysing user behaviour, preferences, and interests, libraries can leverage AI to create customised recommendations for books, articles, and other resources. For example, AI algorithms can analyse users’ borrowing history, reading patterns, and online activities to generate personalised reading lists, suggesting relevant resources that match their interests and needs. This level of customization helps libraries deliver a more user-centric experience, fostering engagement and loyalty among users.

AI is also being used to create virtual personal librarians that provide tailored recommendations and guidance to users. These virtual librarians can understand user queries, recommend resources, and provide information on library services, events, and programs. They can also adapt to individual learning styles and provide interactive learning experiences, making libraries more inclusive and accessible to diverse user groups.

3. Empowering Research and Knowledge Discovery: Advanced Search and Analysis

AI is revolutionising the way users search and analyse information in libraries. With AI-powered search algorithms, libraries can provide more accurate and relevant search results, improving the efficiency of information retrieval. For example, natural language processing techniques enable users to search for resources using conversational queries, making the search process more intuitive and user-friendly. AI algorithms can also analyse the context of users’ queries, understand their intent, and provide relevant suggestions, helping users discover resources they may not have been aware of otherwise.

AI is also enabling advanced data analysis and visualization in libraries. Libraries generate vast amounts of data, including circulation data, user data, and resource usage data. With AI-powered analytics tools, libraries can analyse this data to gain insights into user behaviour, resource usage patterns, and trends in research and knowledge creation. These insights can inform collection development decisions, resource allocation, and service improvements, making libraries more data-driven and responsive to user needs.

4. Promoting Accessibility and Inclusivity: Assistive Technologies

AI is playing a crucial role in promoting accessibility and inclusivity in libraries. Libraries are leveraging AI-powered assistive technologies to make their resources and services accessible to users with disabilities. For instance, AI-powered optical character recognition (OCR) technology is being used to convert printed resources into accessible formats, such as text-to-speech or braille, enabling users with visual impairments to access library resources. Similarly, AI-powered speech recognition and natural language processing technologies are being used to create voice-activated interfaces and virtual assistants, making library services accessible to users with mobility or dexterity impairments.

Blog post by ChatGPT Mar 23 Version. Free Research Preview. ChatGPT may produce inaccurate information about people, places, or facts.

Digital Technology Group theme for 2023 – AI and the impact on libraries – Part 1

This year we have (rather obviously) picked AI as our theme. We hope to share our thoughts and observations on AI tech as it emerges this year on our blog. We kick off with a quick introduction to AI and the impact we think it will have on libraries.

The term AI was first coined in mid-1950’s​ and revolved around high-level cognition​. We often see an interchangeable use of terms​ such as Machine learning, which provides computers with the ability to learn without being pre-programmed​. But AI is what happens when machines work “intelligently”, able to make decisions that maximise the chance of success. ​“AI enables the machine to exhibit human intelligence, including the ability to perceive, reason, learn and interact”  Russel and Norvig (2010)​. Or out another way, “A system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific tasks through flexible adaptation” JISC

Common examples of AI in every day life include;

• Auto-correct; auto-suggest; Grammar check; Transcription; Translation Tools; Automatic writing; suggested search and recommendation.​ These lead to increased productivity but biases in terms of languages available. ​
• Machine learning; natural language processing; voice recognition; image recognition ​
• ​New forms of search and data – text and  Data mining. Chatbots and voice assistants 

The key questions about AI at the moment is how will it impact on libraries? There are a range of issues being discussed, including the practicalities of creating or adopting AI. There are challenges around data description and fragmentation​, or the commitment to preparing training data which requires significant investment of time and resource. It’s recognised that systems are only as good as the design and data underpinning them and this is arguably true of AI. There are also more profound questions about data bias​, data validity​, and data ethics​. As it evolves, AI reflects back our societal concerns and knowledge, from common risks associated with the use lots of energy when we are focusing on sustainability and climate emergency, possible reliance on unpaid and low wage data​, or ‘clickworkers’, all the way to hopes and fears of dystopian and utopian ideals represented in our cultural canon.

The Library and Information world has a unique take on AI.​ It impacts on how and what we teach​ in our information literacy, how we handle enquiries​ in our services, how we purchase, share and organise and access our data and information​. Where we position ourselves in relation to AI, as developers, managers, communities, or educators is vital. In some conversations it is reduced to a simple choice to embrace or resist the technology. Others focus on the complex factors that influence our involvement and contribution. But it is apparent that AI is developing at pace and we must begin to navigate these discussions. We predict that if nothing else, the impact on AI will be to dominate all our professional lives in a far more direct way in the coming years than it has to date.

Digital Technology Group look forward to contributing to the discussions this year!

​

Out of the box or outside the box? DTG AGM 8th Feb 2023

Wednesday 8th February – 1.30pm – 4.30pm – ONLINE

This year’s DTG AGM event is focusing on new technology and library management systems:

Bookings now open!

Hear from speakers about recent implementation projects of a new LMS in their institution, and from Folio – a system which aims to facilitate a ‘sustainable, community-driven collaboration around the creation of a modern technology ecosystem that empowers libraries through open source applications’. Learn about what they see as the future direction for LMS and library technology. Following feedback from last year’s event we will include a break and discussion forum for attendees to reflect and ask questions of the presenters and each other.

This event will be online. £75

We are offering free places for those studying or not currently in work. Please contact our secretary to apply. Secretary.MMIT@cilip.org.uk

1.30-2.00 – Digital Technology Group Annual General Meeting

Out of the box or outside the box?

2.00 – 2.40 –  Our DTG secretary Debbie Morris will be talking about her ‘out of the box’ project with WMS

2.40 – 3.20 – We will hear from Tundun Folami and Lenka Shipton from UWL will describe how they have gone ‘outside the box’ and implemented open source software Koha as their LMS

3.20-3.30 break

3.30 – 3.50 – Discussion forum – A chance to pose questions for our speakers and fellow attendees, share your own experiences of emerging LMS technology and to catch up and network with colleagues.

3.50 – 4.30 Hear about the FOLIO project, which aims to facilitate a sustainable, community-driven collaboration around the creation of a modern technology ecosystem that empowers libraries through open source applications to manage library resources and expand library value. 

Bookings now open!

Below Debbie Morris (Digital Library Service Manager at Leeds Beckett University and DTG’s Committee Secretary) gives us a taster of what she will be speaking about during the event.

(Photo: Leeds Beckett University Library building – Headingley Campus)

A new library system after 20 years (while working from home!)

In Autumn 2019 Leeds Beckett Library began a project to procure and implement a new library platform.  Our previous system was implemented in 2000 and we felt it was time we had a market review to ensure both our users and the university were getting the best value, innovation and functionality available.

The first task was a tender process – drawing up of a list of requirements and key weightings from our stakeholders.  This input and was key to the implementation. As well as library users our stakeholders included IT colleagues, procurement colleagues and library staff.

A Project Team and Steering Group were formed and a tender released in February 2020.

We all know what happened in March 2020….but the advice from university procurement was to carry on with the project unless we heard otherwise, so we did!

We went live, to schedule, in July 2021 and are now in our second full year post go-live.

What did we learn from the experience?

We’ll speak about what we experienced in terms procurement, selection, impact and lessons learned during the event but below are a few tips we will take in to our future systems procurements:

(Photo: Leeds Beckett University Library building – City Campus)

• Utilise the APUC LMS tender framework, a real time-saver
• Have a resource discovery system cross-over if possible – this really helps during go-live and early stages of post go-live
• Make sure there is a test instance prior to implementation
• Agree supplier test accounts for the system with your university IT Department
• Agree additional training with the supplier in the first year to cover specific events in the annual library work schedule.

Good luck with your own implementations – hope to see you at the event in February – if you have any questions, please drop me a line! 😊 d.morris@leedsbeckett.ac.uk

CILIP Conference 2022 – Apply now for a DTG Bursary #CILIPConf22

CILIP Conference The CILIP Conference + Expo (7-8 July, Liverpool) is one of the largest and most eagerly anticipated events in the library and information sector. For 2022, the event has been reshaped and reimagined to be delivered in person and virtually.

DTG are pleased to be able to offer one full delegate place with one night’s accommodation as a bursary place.

CILIP Conference traditionally brings together around 500 professionals from across the sector to share experiences, knowledge and expertise. The keynote speakers include Professor Jacqueline McGlade, Sayf Al Ashqar, and Vanessa Kisuule. The programme is being finalised but you can see an outline of the session content here. Keep up to date by following @CILIPConf22

For the first time in three years, the event will be in person, and will be taking advantage of all the benefits of meeting face-to-face. The sessions will encourage free-flowing conversations, collaborations with like-minded professionals, the sharing of ideas and experiences, as well as being packed with practical tips and inspiring presentations.  There will be more collaborative workshops, more knowledge cafes, more networking and more activity taking place on the exhibition floor.    The theme running through the event will be “Libraries, Information and Knowledge for Sustainability” exploring issues including the circular economy, information literacy, data management, digital tools and evidencing impact.   DTG will be hosting a live tech demo area where conference attendees can drop in an try out some of the tools and tech we have showcased over the last year, attend demos sessions and chat to the committee. We offering a bursary for a keen tech fan who would like to join the committee in staffing our tech zone over the two days. To win the bursary all you have to do is describe your interests and skills, what tech you might be able to demo or support and give us any ideas you can bring to make out tech zone more engaging. The successful winner will also be asked to write us a blog post on their conference experience.

To submit your application for the bursary place, please email Secretary.MMIT@CILIP.org.uk telling us who you are, where you work/study, and telling us how you could contribute to manning our tech zone.  We will subsequently publish the bursary winner’s full blog post.  Deadline for entries is 29 April 2022

We are particularly interested in hearing from people who have never been to the CILIP Conference before, and who wouldn’t ordinarily be able to attend.

Alternatively, early bird discounts are available until 27 May and you can book these directly on the https://www.cilip.org.uk/event/Conf22 website. Remember to log in to the CILIP website before booking so that it recognises your membership status and offers you the correct delegate rate. Early bird tickets are now on sale.

#CILIPConf22 @CILIPConf22