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Artificial Intelligence (AI) in the Event Industry

Will AI, or artificial intelligence, take over the job of event planners?

So, artificial intelligence, like I said, making computers do what they do in the movies, is all about expanding the possibilities of what computers can do, compared to humans.

So, in the early ages of the computer history, humans were mostly responsible for transforming the input in a manner that's understandable for computers.

And as time went on, we sort of got better and better at bringing computers closer to humans, right.

And you've got user experience experts, that all focus on bringing that computer closer to humans.

Well, artificial intelligence today, for instance, is being used in fields like computer vision.

And I remember using those voice interfaces during the early 2000’s and remembering that they were absolute rubbish.

But I don't know if you've tried these Siri's and Android systems recently, it's getting amazing.

Okay, sometimes it's totally off, but, in most cases it's surprisingly correct.

Yes, and that's all thanks to a new, well, a new old technology in the field of artificial intelligence, called machine learning.

So, speech to text, so, when you speak, and a computer converts it to text, is an excellent example of this.

To summarize: they listened for phonemes, which are sounds, instead of individual words, which, sort of, made it easier to recognize sentences.

We, humans, couldn't think up better algorithms for our speech to text systems.

So, all we had to do now, to create better speech to text systems, is to give it examples, right.

Give it examples of speech and then show the system what the output, so, what the text version, what the expected text version should be.

And so, by feeding it loads of data, we are now able to create speech to text systems, that are dramatically improving, simply by feeding it more data.

If we go online and we have to fill in a form, then there's a Google captcha popping up, showing us some images.

So, it used to be that you had to put in weirdly shaped numbers, when you're solving captchas.

The thing that makes, for instance, an AI algorithm offered by Google, different from the same algorithm, offered by a company like IBM or Microsoft or something, is simply the amount of data.

think there was one famous example of a system that beat the Turing test, during, I think it was fifteen-minute conversations.

Because, it, sort of, wanted to steer away the difficult questions, by pretending that it was just an innocent street boy.

Well, during the next five to ten years, you will see at least as many news articles, claiming that there's a new system that beat the Turing test, once and forever.

Yes, of course every industry is going to be using artificial intelligence sometime soon.

There's a famous book, that's about using artificial intelligence to get medical insights.

So, by analyzing large amounts of data, artificial intelligence systems can better predict the behavior of one single person.

So, event planners could use this, for instance, if there's one person that attended, I don't know, three different concerts, by certain rock bands, they can use the information of that one single person, combined with the information of millions of other people, that also attended concerts.

And it can use this information to then make recommendations to this one single person, by looking at the vast amount of information that's available.

So, demographics, getting to know who is attending your events, is one major use case, I think.

If you have a, I don't know, ten thousand people crowd, it's almost impossible to, you know, find one suspicious individual.

You need hundreds of cameras and at least as many police people, to actually look at these images, actively, to actually spot someone.

And a light show, it takes sometimes days and days to program a light show for a concert.

Ask any computer scientist, ten years ago and he would say, like: computers making music, that's...

Moreover, you could even combine this with camera feeds, to actually track how excited your crowd is during the event and use that as a way to dynamically improve the effects of your lights, simply by looking at the mood of the crowd.

Maybe an AI system could look at the total camera feeds of an entire club and look at one single person, who's not having a good time, somewhere in the back.

That's typically what you will hear: people will not pay money to see a computer, they will pay money to see another human, which they can identify with.

If you, one day, create a computer system that could generate, I don't know, excellent techno music.

Instead of having to hire a DJ, to make a nice mix for your party, you could have an AI system that is constantly creating music mixes, even adapting to the crowd moods as well.

We don't want to put our elderly people in boxes, that are completely maintained by AI-systems, right.

It could be that, in the next ten to twenty years, you will see your first live action movie, completely generated by a computer system.

Samsung deepfake AI could fabricate a video of you from a single profile pic

Artificial intelligence developed by a Samsung lab in Russia can fabricate video from a single image, including a painting.  Imagine someone creating a deepfake video of you simply by stealing your Facebook profile pic.

A Samsung artificial intelligence lab in Russia developed the technology, which was detailed in a paper earlier this week.  Here's the downside: These kinds of techniques and their rapid development also create risks of misinformation, election tampering and fraud, according to Hany Farid, a Dartmouth researcher who specializes in media forensics to root out deepfakes.  When even a crudely doctored video of US Speaker of the House Nancy Pelosi can go viral on social media, deepfakes raise worries that their sophistication would make mass deception easier, since deepfakes are harder to debunk.  'Following the trend of the past year, this and related techniques require less and less data and are generating more and more sophisticated and compelling content,' Farid said.

But deepfake technology can also be insidious, such as when it's used to graft an unsuspecting person's face into explicit adult movies, a technique sometimes used in revenge porn.  Deepfake videos usually require a big data set of images to fabricate a fake video of someone, but an artificial intelligence system developed by Samsung created a fake clip from a single picture.  In its paper, Samsung's AI lab dubbed its creations 'realistic neural talking heads.'

The paper was accompanied by a video showing off the team's creations, which also happened to be scored with a disconcertingly chill-vibes soundtrack.  Usually, a synthesized talking head requires you to train an artificial intelligence system on a large data set of images of a single person.

That requires meaningful amounts of training data for both the input video and the target person.  The few-shot or one-shot aspect of this approach is useful, Lyu said, because it means a large network can be trained on a large number of videos, which is the part that takes a long time.

Ask the Expert: Artificial Intelligence in EHS

The SIIA CODiE Awards are the premier awards for the software and information industries, and have been recognizing product excellence for over 30 years.

Here are Martin’s answers to five questions, which give you a great idea of what’s happening with AI, especially regarding the use of AI in workplace safety.

And the fact that it is gradually making its way in the early majority stage means that companies are in a great position to get a competitive edge by adopting AI-enabled solutions, compared to risk-averse competitors who may still be waiting.

Second, according to a Forbes article on indicators of the state of AI, “25% of businesses surveyed have implemented cognitive technologies such as AI or machine learning, either as pilot projects or as long-term strategies”, and “81% predicted growth in AI”.

Leveraging NLP, the solution suggests specific action plans or controls to reduce risks of incidents, that have proved effective in very similar contexts in the past.

This then allows the organization to apply the same corrective or preventive action plans throughout all locations that have similar conditions leading to similar risks.

Imagine if a safety manager had to dynamically identify risk areas, and analyze a large volume of historic data to determine the best response, all in a small amount of time.

If you’re a safety professional, AI will make your job easier, and I believe, even more effective: it drastically increases traditional data processing capabilities, allowing to mine a much – MUCH – greater volume of data, in a much smaller amount of time.

AI leaves much more time for safety professionals to focus on preventive safety programs, as it spares them the time-consuming part of the job which consists in pulling, analyzing and interpreting information from many different data sets, about lagging events.

Also, AI and other technological innovations will free safety professionals to spend more time on advancing shared beliefs, values, attitudes and customs regarding safety. They will be free to focus on what matters most: safety culture.

A common methodology is to look at your model’s recall capabilities – that is, run it against past data, and see how many incidents it is able to capture/predict.

On a concluding note, if you want to learn more about our AI-based solutions and other technological innovations that we’re working on, consider attending one of our SPF events where you can directly see our products in action: SPF Americas in Chicago on June 19-21, and SPF EMEA in Paris on June 24-26.

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