Programme Handbook and Canvas Statements Relating to the use of Generative AI Tools
Amid intensified interest, the frenetic launch of diverse off-the-shelf pre-trained LLM models and platforms by technology giants sets a new trajectory of AI adoption in the industry to enable democratized access to
generative AI for business firms. The platform leverages AI algorithms to automatically generate code snippets and templates, assisting software developers in their coding tasks. Enterpret’s technology speeds up the development process, improves code quality, and reduces the potential for human error. With their AI-powered code generation, Enterpret aims to empower developers to focus on higher-level tasks and accelerate software development. Hugging Face is a leading platform for natural language processing and generative AI models.
From understanding its fundamental principles to exploring real-world use cases, we will provide you with the knowledge you need to navigate the dynamic landscape of generative AI in the insurance sector. Generative models learn from real-world data to create synthetic data sets, so the information they produce will act the same in another algorithm. Consequently, the resulting data sets are relevant, effective, and safe all at the same time.
A Short Summary of the Impact of Generative AI on HR and the People Function
This can help recruiters ensure that job descriptions are written in a way that attracts the right candidates and accurately represents the position. Align already had a construction schedule in place that helped it win the C1 project, but used ALICE to double-check its assumptions and look for opportunities to improve the plan for its viaduct substructure work. Scheduling a massive infrastructure project, with its complex interdependencies and constraints, is hard to do well. The construction simulator incorporates those interdependencies in an algorithmic equation that can analyze thousands of scenarios and evaluate them based on the company’s goals. Choice Hotels has lagged behind its competitors in Environmental, Social, and Governance (ESG) efforts to date, but this could help the company make up some ground. Think of this tool as a robo-adviser, but instead of making stock picks (another well-known AI application), it makes suggestions for managing the environmental impact of the company’s portfolio of properties.
- Generative AI can analyse network patterns, predict potential cyber threats, and suggest preventive measures.
- For instance, a well-known financial services company used a generative AI language platform to personalize its ad messaging, resulting in a 15% conversion rate increase.
- Generative AI broadly refers to machine learning models that can create new content in response to a user prompt.
- This can help healthcare providers reduce costs and improve the quality of care they provide.
The capabilities of generative AI are vast – perhaps better illustrated by the prompt, “a grapefruit drinking coffee on the beach in Provence”. EU data protection authorities have also recently started to look at some generative AI providers. In March 2023, the Italian data protection authority (Garante) blocked ChatGPT’s processing of personal data (effectively blocking the service in Italy) until ChatGPT complies with certain remediations required by the authority. In April 2023, the Spanish data protection authority (AEPD) initiated its own investigation.
Where you include any material generated by an AI program, it should be cited just like any other reference material. Alongside your assignment you should also upload a commentary detailing how generative AI has been used to develop your submission. Further guidance on how to do this can be found here [Insert link to School-based Canvas page]. Whilst AI tools, including ChatGPT, can assist you with idea generation and research, it is important you are aware of their limitations.
For instance, in the last few months online, AI has been used to mimic the voices of famous singers performing different artists’ songs. So far, Freddie Mercury’s voice has been used to sing Celine Dion’s My Heart Will Go On, while an AI Taylor Swift has performed Kanye West’s Heartless, among many other examples. Imagine a world where machines can create art that rivals the works of renowned human artists, compose music that evokes deep emotions, or write stories that captivate readers. Commentators and “futurists” seem assured that one day AI will join or replace human Directors and will be running corporations and making decisions autonomously.
UK at risk of falling behind in AI regulation, MPs warn
GenAI must be used ethically and in compliance with all applicable legislation, regulations and organisational policies. Users must not use GenAI to generate content that is discriminatory, offensive, genrative ai or inappropriate. If there are any doubts about the appropriateness of using GenAI in a particular situation, users should consult with their supervisor or Information Governance Team.
With the publicity surrounding generative AI tools and free and easy access to a number of high-profile generative AI tools, some employees will inevitably start to experiment. For example, fund managers consulting these tools to help make informed decisions on investment strategies creates risks if such users are inputting potentially confidential information into them. This is because some AI tools permit the retention of such input data in order to fine-tune the AI (this is the process of taking the additional data provided in the input and using it to improve the AI model by adding it to the original training data). This could result in the input information being replayed back to new users in the form of outputs which may be competitors of the fund manager. This could also lead to concentration risks if multiple users are making similar investment decisions or recommendations based upon a small number of technologies.
Confidential and personal information must not be entered into an GENAI tool, as information may enter the public domain. Users must follow all applicable data privacy laws and organisational policies when using GenAI. If a user has any doubt about the confidentiality of information, they should not use GenAI. All information generated by GenAI must be reviewed and edited for accuracy prior to use. Users of GenAI are responsible for reviewing output, and are accountable for ensuring the accuracy of GenAI generated output before use/release.
In right-wing politics Fauci has garnered significant opposition, and the intention of the attack ad is to strengthen DeSantis’ support base by portraying Trump and Fauci as close collaborators. In recent months there have been a number of instances of genrative ai deepfakes have been created using generative AI. With deepfakes becoming not only easier and cheaper to produce but more realistic and harder to determine if they’re fake, the potential for them to be used for malicious purposes is growing rapidly.
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We do this, among other things, through internal seminars and through networking with industry colleagues, in Sweden and within the European public service cooperation EBU. For example, following the launch of OpenAI’s foundation model GPT-4, OpenAI allowed companies to build products underpinned by GPT-4 models. These include Microsoft’s Bing Chat, Virtual Volunteer by Be My Eyes (a digital assistant for people who are blind or have low vision), and educational apps such as Duolingo Max, Khan Academy’s Khanmigo .
But ChatGPT is just one of many applications for generative AI, and as businesses either embrace or avoid the technology, it is creating both new risks and exciting opportunities. How do you balance these risks with the massive opportunity presented by generative AI? The starting point must be understanding the potential risks, balancing them against the opportunities and developing appropriate policies and guidelines. With over 25 years combined experience, we bring companies together to synchronise into strong corporate partnerships.
For instance, in chatbots, generative AI models can be used to generate responses that are more human-like and contextually appropriate for different user inputs. These models can be trained on large amounts of conversation data to learn patterns of language use and to generate responses that are more likely to be relevant and engaging for users. Generative AI algorithms can adapt the learning experience based on individual progress and performance. AI can dynamically adjust the learning materials’ difficulty level, pace, and content by monitoring employee interactions, quiz results, or assessment outcomes. This ensures that employees are appropriately challenged and engaged, optimising their learning outcomes.