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Q&A from the AI Revolution: Implications to Business and Society

At the AI Revolution seminar on 9 November 2023, we got a lot of questions through Presemo that we didn't get to answer. So, we used AI to organize them and then had the AI answer them. Check out how well it did and feel free to comment. We used the paid version of ChatGPT with GPT-4 to do this. The event was organized by the Department of Industrial Engineering and Management and supported by Aalto Networking Platform.

Tero Ojanperä on stage at the AI Revolution seminar on 9 November.

Ethics and Responsibility in AI

How could we educate the user about the technology they're using, its risks and the safe and responsible usage?
Implement interactive tutorials within AI services and platforms, and provide clear, user-friendly documentation outlining risks and best practices.

How do you see the risks of use of genAI to create disinformation campaigns and how can we tackle that?
Invest in digital literacy programs and AI detection tools, and establish a regulatory framework to manage and mitigate the spread of AI-generated disinformation.

Do you recognise AI-generated content as a threat used in hybrid war? How can we fight back against massive amounts of news released which are spreading misinformation?
Yes, it's a threat. Combating this requires international cooperation to establish standards for content verification and the deployment of advanced fact-checking AI.

Based on which ethics firm's data should be governed and what kind of data can be used in an AI application (e.g., customer data is very sensitive)?
Data governance should be based on ethical frameworks that prioritize consent, privacy, and the individual's right to control their personal data, especially in sensitive cases.

Strategic AI Integration in Business

On a grass-root level, how should organizations - such as a consumer goods business, as a technology user - start unraveling the opportunities of genAI
Start with small-scale experiments focused on specific business challenges and scale up based on the insights and value generated from these initial tests.

3 concrete steps for organizations 1) have AI info sessions: what AI is today, what it is not yet 2) have AI jams: let people try AI common platforms and simultaneously brainstorm wild ideas for data boosted business 3) build your first own solutions - learn from mistakes. Measure the delivered value and move on.
These steps are indeed effective. Education leads to informed ideation, which, coupled with practical experimentation and analysis, can drive successful AI integration.

AI Talent and Skills

What kind of talents are regarded as AI “talents” being wanted?
AI talents typically include expertise in data science, machine learning, AI ethics, and domain-specific knowledge, along with problem-solving and critical-thinking skills.

How about the mental health of the technology creators? How can we make sure of the well-being of those who are holding the AI technology in their hands, both for their own and for the tech users' safety?
Organizations must prioritize mental health by offering support programs, encouraging work-life balance, and fostering a culture that recognizes and mitigates work-related stress.

AI's Societal Impact

With AI, robots, metaverse + other tech people, employees, companies and societies will get superpowers! The question is, how we will use these superpowers?
These 'superpowers' should be used to tackle global challenges, enhance quality of life, and drive sustainable development while ensuring equitable access and benefit-sharing.

Is AI only one of the means to hype - or gaslight - diversity and equality while reality remains as it has been for centuries?
AI has the potential to both challenge and perpetuate existing social structures; it's up to us to use AI to promote genuine diversity and equality actively.

AI in Research and Development

How near are we on connecting AI with a general model of the physical reality
We're making strides, but fully integrating AI with a general model of physical reality is complex and requires further advances in AI's understanding of the physical world.

The creative destruction will speed up and many people, companies and organization (also in Finland) need to reinvent themselves in the next 3-5-10 years.
Creative destruction is a catalyst for innovation. To adapt, entities must embrace change, foster a culture of continuous learning, and remain agile in their strategies.

AI Technology and Innovation

Biggest threats in journalism?
The biggest threats are the erosion of public trust due to misinformation and the challenge of maintaining journalistic integrity in the age of automated news generation.

What do you think about the impacts of AI on academic publishing? If AI translation is just as perfect, does that mean we can simply work in our native language and have AI translation for publication?
AI could democratize academic publishing by breaking down language barriers, but it will not replace the need for nuanced, expert-driven editing and review processes.


Should robots be taxed in the future and should they have the right to strike?
Taxing robots is a debate around compensating for automation's economic impact. As for striking, it's not applicable as robots lack consciousness.

Who should own the data of SMEs' AI applications; SMEs or companies providing the applications?
Ideally, SMEs should retain ownership of their data when using AI applications, with clear terms set out in agreements with application providers.

How can we train AI to be unbiased, with a neutral opinion?
Training AI for neutrality involves using diverse data sets and ongoing testing for biases, plus incorporating feedback loops for continuous improvement.

As AI changes the balance between capital and the working input of people, how should it be reflected in taxation and redistribution of wealth?
Taxation and wealth redistribution policies may need to evolve to address the new economic dynamics introduced by AI, ensuring fair benefits for all.

We are talking about governance but aren't we late for this? GPT Models are already out, so how do we govern it now?
It's not too late for governance; regulations can still be developed and applied to existing and future AI models to guide ethical and responsible use.

What will come after AI?
It's challenging to predict post-AI technology, but it may involve more advanced intelligence systems that further blur the lines between human and machine capabilities.

More information

See highlights, presentations and photos from the event here

Keywords: AI revolution, Aalto University, AI impact on business and society, AI and creative industries, Ethics of AI, Future of AI

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