Digitalization

Artificial intelligence is going to change the world—but there’s still a lot of hype and hot air around it.

Understanding what’s fact, what’s fiction and what’s marketing spiel is essential if you want to take advantage of it.

One claim that’s being made with increasing frequency is that machine intelligence will, at some point, perhaps soon, surpass human intelligence.

This is known as the “singularity” and is important for many reasons, chief among them being that it will mark the first point in human history that we will share the planet with entities that are smarter than us.

But is it really likely to happen? Or is it just a concept created by technologists and futurists to sell us a vision of the future where they end up making a lot of money? Let’s take a look.

What Is The Singularity And How Far Off Is It?

The concept of the singularity was popularized by science fiction author Vernor Vinge in the 1990s. It stems from the idea that once machines are able to learn for themselves, they will inevitably, at some point, surpass humans in every way that we are able to benchmark intelligence.

There are many facets of what we call “intelligence.” Two are memory and ability to calculate, and machines have long outpaced us at both of these. Now, with the emergence of new forms of AI, they are becoming creative, communicative, capable of advanced language skills, and even reasoning, problem solving and exhibiting emotional intelligence.

Proponents of the singularity theory point out that machine intelligence has the potential to accelerate exponentially. As AI gets smarter, it will be able to design even smarter AI by itself, with no need for input from us.

They also point out that it could have highly unpredictable consequences. Can we trust it to always have our best interests at heart? Will it develop feelings of superiority or self-preservation that will make it a risk to us? Many very intelligent people think this is a real danger.

On the other hand, a more optimistic view is that it could usher in an era of unprecedented technological advancement, as super-smart computers come up with solutions to every problem facing the world, from the environmental crisis to curing cancer. Some believe that it may be able to make us immortal.

The singularity may not arrive tomorrow, but it may not be that far off earlier. Renowned futurist Ray Kurzweil predicts that it may arrive between 2029 and 2045, based on the current rate of progress being made by AI research and factoring in concepts like Moore’s Law.

Others, including Rodney Brooks, founder of iRobot and former head of computer science and AI at MIT, think this is unlikely. Their argument is that the computer power needed to realize a super-human internet is still centuries away.

And some, such as the psychologist Steve Pinker, doubt it will ever happen, stating that the fact we can conceptualize it happening is no evidence that it ever can or will become a possibility.

The Last Mile?

Given the recent advances we’ve seen in AI—most notably the emergence of generative AI tools like ChatGPT and Dall-E 2—it might seem to many of us that we are not very far from the singularity at all.

But even if this is the case, there are still some very challenging hurdles that need to be overcome before it can become a reality.

It’s true that current systems have capabilities that just a few decades ago would only have existed in science fiction. For example, engaging in conversations, writing poetry, outperforming humans at complex games like Go and accurately describing what they’re able to “see” thanks to computer vision.

But today’s AI is still “narrow”—usually designed for one particular task or set of tasks. A major milestone on the road to super-human intelligence will be the development of artificial general intelligence, which is capable of taking what it learns about one task and applying it to learn how to do many different tasks, much like we can.

There are also technical challenges remaining. Computational resources far beyond those available today will be needed to train machine learning algorithms that can “think” in as broad a range of ways as human beings can. And humans are also hugely more efficient when it comes to processing data. Machines need huge volumes of information to learn even relatively simple jobs, whereas we can pick up the basics of many tasks simply by watching them being performed once or twice, thanks to our ability to think “generally” and apply a method of thinking that we refer to as “common sense.” This comes from the implicit knowledge we have of the world and how it works.

Of course, it’s probably foolish to think that these last-mile hurdles are in any way insurmountable, particularly given what’s been achieved so far. But it’s far from certain that they will be cracked any time soon.

So, Should We Be Preparing For The Singularity?

Though the timelines may be uncertain, it seems prudent that we should be making preparations, given the potentially seismic consequences.

One of the most obvious guardrails that should be in place is taking action to ensure that AI will always act in alignment with human values. This will involve making sure that it understands concepts such as respect for the sanctity of life, freedom, tolerance and diversity. Limiting the ability of AI to cause harm through bias, unethical decision making, or rampant profiteering on the part of businesses or governments that deploy it is an essential step.

At the same time, measures should be put in place to mitigate the societal harm that could be caused due to factors such as job losses to AI. This might involve encouraging companies that are replacing human staff with machines to invest in reskilling and retraining staff for alternative roles and exploring economic policies such as the universal basic income.

While it’s far from certain when, or indeed if, the singularity will occur, the stakes are high enough that we should be treating it as a very real possibility. By keeping alert to the risks and ensuring safety, transparency and accountability are central to AI implementation strategies, we have the best chance of ensuring AI evolves in a way that will benefit humanity rather than harm it.

By now everyone’s probably seen generative AI tools like ChatGPT and Midjourney that can create text, drawings and even computer code that look like they’ve been made by humans.

They’re highly impressive, but are you just using them for fun, or have you worked out how to get them to do something that’s truly useful?

Well, one of the areas where they have the most potential is automating day-to-day workplace tasks. In the last two years, many new apps, tools and services have appeared that can help us become quicker and more productive at work.

So here’s my roundup of what I believe are some of the most impressive, useful or innovative generative AI productivity tools available today. They can help anyone to do their job quicker or more efficiently, saving valuable time that can be spent on more rewarding and creative tasks. These are in no particular order, but let’s start with five that I think are particularly interesting or noteworthy:

Zapier

Zapier is an integration tool, which means it helps other tools and applications talk to each other and work collaboratively. For example, it can be used to automatically log information from sources like call logs, emails, or chat transcripts. It can also be used to create to-do cards in project management tools like Trello, calendar events, or update records in CRM software like SalesForce or Hubspot. This can save users huge amounts of time that would be spent copying and updating records across different platforms. It also reduces the chances of human error.

Zapier has now integrated generative AI chatbots that make this process as simple as telling them what you want it to do. It will automatically find the right connectors and triggers and pull out insights from real-time business data. This makes it simple for anyone to build AI workflows involving multiple applications and data sources.

Otter.ai

In recent years, Otter has emerged as one of the leading AI-powered meeting assistants. It can automatically create transcripts of conversations that can be organized and searched, as well as extract insights and action items. It integrates with popular messaging and meeting apps like Zoom and Teams and can generate email summaries and send them out to relevant people while keeping track of any follow-ups that are needed. One of the things that set it apart is its high level of user-friendliness, meaning that even colleagues who are nervous about trying out new tools should be able to start making use of its AI features very quickly.

Trello

Millions of people use project management tools to keep track of ongoing work or measure progress toward goals, and Trello is one of the most popular. Like many industry standard tools, it’s recently been powered up with the inclusion of generative AI features, in this case provided by the Atlassian Intelligence engine. This streamlines the process of creating new cards by generating content and automated summaries, as well as even suggesting improvements for grammar or clarity when communicating your ideas. Atlassian Intelligence is only available to premium and enterprise Trello users at the moment but may be integrated into the free version in the future.

Zoom With AI Companion

Zoom established itself as an everyday tool during the Covid-19 pandemic, helping many companies carry on with business (almost) as usual. Many more of us discovered it was also a great way to keep in touch with family and friendship groups. More recently, it, too, has received a generative AI makeover thanks to the addition of Workplace Companion.

With this, users with a paid subscription can create automated summaries of calls and virtual meetings, along with follow-ups, assignments and action points. This eliminates the need to take notes and other manual administrative actions during meetings and lets attendees focus on the discussion at hand.

BeeDone

BeeDone takes a different approach to many of the productivity apps here by gamifying the process of task management. It does this by breaking complex tasks down into simple steps and then awarding points for completing them. It’s a fun idea that adds a new spin on the numerous “smart” to-do lists, task managers and time trackers that are available. BeeDone learns users’ habits and fine-tunes its ability to optimize processes and even includes “productivity tournaments” where users can compete against each other to see who can become the most efficient.

More Great Generative AI Workplace Productivity Tools

There are many more tools that let anyone put generative AI to work to streamline routine workday tasks; here are some more of the best that I’ve come across:

• Asana automates project management and workflow tasks and manages calendars.
• Avoma AI meeting assistant transcribes meetings but also provides coaching insights to help users improve their communication and engagement skills.
• Beautiful transforms ideas into fully realized slides and presentations with automated design features.
• Clara is an AI assistant that aims to act as a virtual employee, scheduling meetings, communicating between attendees and adding details to your calendar once they’ve been established.
• ClickUp is a generative AI-driven workplace productivity suite with project management, time tracking, whiteboarding, agendas and other features.
• Clockwise is a time-management tool that can automate scheduling to help teams make more efficient use of their time.
• Decktopus generates slide decks and presentations from natural language prompts.
• Duet is another Google service built into Workspace to provide a collaborative assistant for productivity tasks.
• EmailTree email management and customer service platform has features like automatic reply suggestions, multilingual support, team management, CRM, sentiment analysis and automation.
• Fireflies transcribes, summarizes and searches voice conversations.
• Gamma automates the creation of presentations and various types of documents with the help of generative AI.
• Mailbutler integrates with common email applications to provide tools that automate composing, summarizing and responding to emails.
• Notta provides AI note-taking and audio transcription.
• Notion is an AI-powered workspace that manages tasks and offers functions like document summarization and content creation.
• Reclaim provides AI-powered calendar management and time tracking.
• Sanebox offers AI-powered email management that analyzes incoming mail, sorts it into relevant folders and generates reminders and auto-responses.
• Tome leverages AI storytelling to create compelling decks and presentations using GPT-4o technology.

Education is changing rapidly. In today’s fast-moving world, a model where we graduate in our youth prepared for a lifelong career is simply no longer valid.

Technology is reshaping the world into one where ongoing training, upskilling and reskilling are a necessity – and education is transforming to cater to this. Artificial intelligence (AI), online learning and breakthrough technologies like virtual and augmented reality (AR/VR) already play an increasingly important role. They will all become more integrated into the way we study and learn over the next decade.

So, here’s my look-ahead to what I believe will be the dominant trends in education and educational technology (EdTech) by 2035. It may seem a long way away, but understanding them now will likely help us prepare for a future that, thanks to technology, will look very different than today.

Immersive Virtual Learning Environments

By 2035, the distinction between the physical and digital worlds will be increasingly blurred, and this is as true in education as anywhere. While I am sure many children and teenagers will still be attending brick-and-mortar school, alternatives will be well established for those who can’t, as well as for adults and lifelong learners.

VR and AR technology will be far more accessible than it is today, with lightweight and affordable devices making it easy for anyone to interact with tutors and fellow learners as if they were in the same room. Highly immersive virtual classrooms and campuses will mean we can participate in sophisticated simulations, engage in complex scientific experiments or explore ancient civilizations first-hand.

The maturing of technologies that exist today will democratize access to education for those who aren’t fortunate enough to live in areas with good schools and colleges. However educators will face the challenge of balancing this with concerns such as increased social isolation and the impact of extended screen-time on developing minds.

AI-Driven Adaptive Learning

AI is going to change education (and everything else) in many ways, but over the next ten years, one of the most profound effects will be the rise of personalized learning. As the number of learners in both traditional classrooms (particularly in the developing world) and online environments climbs, teachers will have access to tools that accurately assess abilities and differentiate between learning styles to create hyper-personalized curriculums tailored to individuals’ requirements.

Today’s AI tutoring platforms will evolve into flexible AI mentors, able to understand psychological states and behavioral patterns to determine the best teaching strategies and even provide emotional support and encouragement. Students will have access to insights derived from biometric data to help them recognize the best time to learn and when they should rest. Adaptive gamification will challenge learners to improve themselves by dynamically engaging and assessing them throughout the education process, perhaps putting an end to the stress-inducing routine of cramming for end-of-term exams.

Personalization at this level has the potential to help us learn better and attain better educational outcomes. However, there will also be big challenges around privacy and questions over the role of human teachers as they find their role transitioning from information providers to learning facilitators. Biased data could lead to learners being inaccurately assessed, and care must be taken not to overlook the importance of human oversight and mentorship.

Neurotechnology And Accelerated Learning – Hacking The Human Brain For Better Learning

Here’s where things get very science fiction. So, brain-computer interfaces (BCIs) are in development today – the most famous example being Elon Musk’s Neuralink experiments. Don’t worry; we probably won’t all have to have chips implanted in our heads to benefit, though, as non-invasive forms of BCI have also been in development for some time.

The first use cases in education are likely to involve assisting students with disabilities, enabling them to control devices with thoughts. This will enhance their ability to communicate and take part in learning activities.

Within ten years, they could also be used to understand the brain’s learning processes better, potentially speeding up our ability to ingest, retain and recall information. By monitoring the electrical feedback generated by the brain, researchers believe it may be possible to optimize our ability to learn information and even develop skills such as playing a musical instrument.

Will this really be mainstream within ten years? Well, a lot depends on the outcome of research that’s going on today. And just as importantly, it will come down to how society is able to answer questions around the ethical and security implications of developing technology that can literally read our thoughts!

A Lifetime Of Learning

The concept of a “job for life” might have seemed normal to our parents’ generation, but it’s obsolete today. Students graduating ten years from now will be under no illusion that they are equipped with the skills and knowledge they will need for a lifelong career. The accelerating pace of digital transformation will make it necessary for those who want rewarding careers to adapt to new models of ongoing, continuous education. Education systems will adapt to support this, offering more courses that will involve on-the-job training and opportunities for upskilling.

It’s already becoming normal for big companies like Amazon to offer degree-level apprenticeship programs, and this will become more common as employers seek to develop workforces equipped with the skills they need. Opportunities will involve online learning, modular learning and the type of immersive virtual learning discussed elsewhere in this article. Micro-learning and nano-learning will deliver education in bite-sized chunks, capable of being rolled out on a “just-in-time” basis to meet the changing needs of industries and professions. To cater to this, education providers will offer subscription services, allowing us to dip in and out of schooling in accordance with our personal needs. While there will always be a need for STEM education, with computers becoming increasingly proficient at technical tasks, more learning will be focused on human-centric “soft” skills that will increase our chances of remaining relevant in the era of AI and automation.

credit: bernardmarr

2024 is a big year for democracy, with over two billion of us voting in elections across the US, India, the EU, the UK and many other countries and territories.

But if you’re heading to the ballot box this year, would you consider voting for an AI candidate?

Or how about letting an AI pick the best candidate to lead you?

And have you considered to what extent AI is going to affect the outcome of polling and influence the choice of voters?

These are all ways that AI is playing an increasingly prominent role in elections, democracy and governance, just as it is in every other area of life. So let’s explore some of the potential ramifications of this on the events of 2024 – the year that AI and elections collide in a big way!

Virtual Politicians

Virtual politicians, as well as political parties driven by AI, are now appearing on ballot boxes around the world.

In Brighton, UK, citizens will have the opportunity to vote for “AI Steve”, an avatar created by businessman Steve Endacott. Voters can chat and interact with Steve, questioning him on his policies on issues ranging from local housing to LGBTQ rights.

Steve will then formulate policies based on these interactions as he attempts to represent the views and values of his (potential ) constituents.

Apparently, not everyone is convinced, with one local resident telling Reuters, “AI and politicians have one thing in common: they can’t be trusted.”

Steve is not the first virtual politician. In New Zealand, SAM, created by software developer Nick Gerritsen, was built to answer questions from constituents on social media. And Alisa ran against Vladimir Putin in the 2018 Russian elections with the mission of creating “the political system of the future, built exclusively on rational decisions made on the basis of clear algorithms.” Alisa seems to have since disappeared.

In Denmark, another experiment in fusing AI and democracy was spearheaded by The Synthetic Party, founded by philosopher Asker Bryld Staunæs. The party generated policies via machine learning based on texts created by Danish fringe parties since the 1970s, with the aim of creating a party that would represent the views of the 20 percent of Danes who don’t vote.

The companies that make this all possible by building AI have proven to be a stumbling block for some AI would-be politicians, however. ChatGPT creator OpenAI recently banned an AI candidate built on its technology from running in a US mayoral election, stating that it broke its user license by engaging in political campaigning.

The Influence Of AI Algorithms

Even if we wouldn’t choose to vote for an AI politician, would we consider letting AI choose who we should vote for by deciding which human candidates best represent our views?

Or, to take a more sinister view – could this already be happening without our knowledge?

This is the view taken by Yuval Noah Harari. Harari has argued that AI has already been pivotal in influencing our choices due to the all-pervasive algorithms that serve us content on social media. These algorithms, designed to keep us engaging with platforms, may feed processes like confirmation bias, providing subtle impact on our thoughts and actions which could have significant impact on our decision-making at the ballot box.

In his book Homo Deus, Harari even suggests that perhaps AI should vote for us due to its ability to deeply understand our beliefs and preferences and then match us with parties and candidates that are most likely to make us happy.

Deepfakes And Disinformation

We have seen algorithms being leveraged to deliberately spread disinformation in previous elections. However in 2024 more people than ever have access to powerful tools and technologies that can be abused in this way.

Deepfakes in particular – synthetically generated video and audio that can mimic the likeness of a real person – pose a real threat to democracy. Highly convincing videos of politicians, including Joe Biden and Rishi Sunak, have already spread far and wide. Some are humorous, ridiculous and most likely harmless, such as Nigel Farage blowing up Rishi’s Minecraft house. However, there is clearly the potential for damage to the reputation of politicians, particularly if the content is targeted at those with low levels of tech literacy.

Efforts to mitigate the threat involve technology – creating tools that can detect deepfakes, and legislation – China’s recently introduced AI laws make it a crime to portray someone falsely. Education, however, is likely to be the most critical measure, ensuring the public are aware of what can be done with AI, and that not everything they see online, even in videos, is true.

AI And The Future Of Democracy

As AI continues to become more sophisticated and pervasive, its potential to influence and perhaps endanger democracy will only increase.

Though we may not yet be ready to vote for AI politicians, The concept serves as an interesting experiment in the power of technology and the direction society may be heading in.

As with many other professions, AI will certainly be harnessed by politicians and candidates to make their jobs easier. They will be able to make data-driven decisions that align with the interests of those they represent, analyze and draft proposals, manifestos and legislation, and create personalized messaging that may enable them to target individual voters more effectively.

And as voters, we will leverage it to gain insights into how well parties and politicians live up to the standards we expect from our elected representatives.

However there are also important ethical concerns that will need to be addressed around accountability, transparency, and the requirement for robust legislative frameworks to prevent the spread of misinformation.

By addressing these issues now, we can ensuring AI evolves in a way that is beneficial to the concept of democracy as a whole, encourages politicians to take actions we agree with, and helps us all make better and more informed political choices.

Today, the term “iPhone moment” is frequently used to refer to a technology breaking through into the mainstream. The release of Apple’s first phone back in 2007 marked the beginning of the smartphone era – from then on, it became normal for everyone to go about daily life with a powerful, internet-enabled computer in their pocket.

The effect this had on society was huge. Although the internet, online shopping and social media had been around for a while, they were generally confined to desktop computers. This meant that only those with access to a computer, either at work or in the home, were onboard with the online revolution. Suddenly this was no longer the case and the internet was available to everyone, everywhere.

Apple’s recent announcement that it has partnered with OpenAI to bring ChatGPT-style services to its mobile devices (as well as its desktop computers) could well be the “iPhone moment” (literally) for generative AI.

If your work, business, or interests revolve around technology, there’s already a good chance that you’ll be using generative AI daily. However, for everyone else, recent research suggests that it hasn’t quite cracked the mainstream.

But that could be about to change if the average smartphone user is about to receive a major AI-powered makeover. Integrating generative AI into the pockets of millions of people in a way that seamlessly fits into their everyday lives could be as transformative to society – if not more so – than the arrival of internet-enabled phones. While this has the potential to be hugely democratizing and empowering in amazing ways, it could also present some tough challenges.

What Is A Technological “iPhone Moment”?

An iPhone moment is more than just a technology suddenly becoming hugely popular. The genius of Apple’s vision was to create a device that was so intuitive and user-friendly that anyone who saw it immediately realized that it could change their life.

It set new standards for user experience and functionality and ushered in the “app economy,” introducing the app store, where a tool for just about any task could be found.

There are already hundreds, if not thousands, of generative AI tools and applications. Still, they’re mostly targeted at business, creative or technical use cases, and people might not immediately understand how they would fit into their lives. General-purpose tools like ChatGPT, on the other hand, might appear to be too broad and lack specific functionality that people would find useful day-to-day.

If anyone can create the shift in perception necessary to change this, then history suggests that it’s Apple. Integrating it across the suite of tools that millions use every day for keeping in touch with friends, shopping, navigating, and entertainment could easily be the move that brings AI to the masses. For example, Siri is one of the most widely used personal digital assistants in the world, and supercharging it with AI could normalize human-to-machine conversations that go far beyond the “voice command” model we’re used to today. And how about giving Apple Music or Apple Navigation the ability to chat away with users, helping us choose what music to listen to or what route to take in a conversational way?

By making AI more user-friendly and obviously useful, the partnership between Apple and OpenAI has the potential to create a transformational shift in society’s relationship with technology. But it could create some pretty big problems, too …

Is AI Ready For The Mainstream?

So AI today certainly isn’t without its problems, and the danger of everyone suddenly starting to use it is that those problems could be magnified in some scary ways.

Let’s start with a big one – the environment. It’s an unavoidable fact that AI today uses huge amounts of energy and also generates a worrying amount of emissions. If it goes mainstream and millions more of us are using it every day, that’s only going to increase. This would create huge problems for a world where reducing our carbon footprint is a priority.

Then there’s the problem of AI hallucination. Anyone who has used a tool like ChatGPT for any length of time will have realized that it sometimes makes things up. While this isn’t always a problem when we’re using it in a limited way for drafting emails, for example, which can easily be proof-read and fact-checked, it could be more of a problem if millions of people are suddenly using it for day-to-day activities like navigating journeys, reminding them to do important things, or managing their daily schedules.

On top of that there are issues of privacy and data security. How do we ensure that casual, everyday users understand the risks of putting personal data into opaque and often unaccountable AI systems with little understanding of how it’s going to be stored, processed and shared?

If Elon Musk – one of the original founders of OpenAI – is now threatening to ban Apple devices from his workplaces due to his concerns over privacy, it’s probably a problem we should take seriously.

Unlike its rivals, Apple didn’t have a (publicly available) generative AI of its own before the announcement of this partnership. So, it makes sense that it would want to work with OpenAI – the breakout star of the generative AI revolution.

But just as the mainstream adoption of the internet and smartphones brought challenges that society is still facing, so too will the integration of generative AI with everyday life.

We can take some reassurance from the fact that Apple has a relatively good track record when it comes to safeguarding user privacy. But will it be able to mitigate the risks of massively scaled AI hallucination and carbon emissions?

For better or worse, this is a partnership that’s likely to lead to big changes for us all. Addressing these challenges will be critical to ensuring the mainstreaming of generative AI takes place in a way that’s beneficial to us all without doing further harm to society or the planet.

Real estate agents and other professionals in their industry are in the business of selling good old-fashioned solid bricks and mortar. But that doesn’t mean their jobs aren’t impacted by new technology.

Digitization, the internet, and more recent trends like drone photography and virtual reality have all made a big impact. But bigger changes could be on the horizon as agents, appraisers, investors and mortgage brokers race to benefit from the opportunities of generative AI.

A recent McKinsey report estimates that the hottest tech trend of moment could generate up to $180 billion in value for the real estate industry. This means that it’s inevitable that the roles of professionals will change as they adopt new working practices and learn to augment their abilities with new, generative tools. With this in mind, lets take a look at some of the changes that we can expect to see.

Generative AI And The Real Estate Business

Generative AI has the potential to transform many of the day-to-day tasks carried out by real estate professionals. For example, it can quickly generate property descriptions and listings to entice potential buyers. This could involve using computer vision to analyze photographs, floor plans or even video captured by drones and translating them into written descriptions. These descriptions can even be personalized to appeal to individual customers.

If a property doesn’t exist yet because it’s still being built, then AI could create images to show to off-plan buyers or even VR/ AR environments to demonstrate buildings via three-dimensional walkthroughs.

Chatbots can assist with customer service, taking care of basic and questions from potential buyers, as well as automatically scheduling tours and viewings.

Property brokers and investors will benefit from using generative AI to analyze market trends and property values, providing data insights into investment opportunities in natural language. Generative AI will also analyze documents to automate many of the repetitive tasks necessary for due diligence and risk assessment.

Those whose jobs involve appraisal and valuation will spend less time gathering and analyzing information as generative AI automates the process of identifying comparable properties and other factors that will influence property prices. This will augment the abilities of the automated valuation models (AVMs) that are widely used today, making them more powerful and accessible. Apps like Zillow are already available that can provide property price estimates based on photographs and data such as location and square footage.

Mortgage brokers will streamline the process of dealing with loan applications by automating administrative tasks involved with underwriting and assessing applicants’ eligibility, as well as detecting fraudulent applications. It will also help brokers to offer more personalized loans tailored to fit their clients’ requirements.

Ethical Considerations

Access to housing and equitable housing markets is important to society, which is why many governments implement stringent legislation around the buying and selling of property. Real estate agents, brokers and other industry professionals must be aware that they will be accountable if using generative AI puts them in breach of local laws and regulations.

When using AI for marketing purposes, care must be taken to avoid the dangers that can be caused by biased data. This is particularly important when carrying out checks such as affordability assessments, where bias present in training data could have negative social consequences.

When AI is used to make decisions that can impact the lives of customers, then care must be taken to protect personal data, as well as ensure they consent to it being used. Use of generative AI should be transparent so buyers and prospective buyers know how decisions are being made.

Additionally, when AI-generated visuals and other content are used to market properties, it should be made clear that what a potential customer is looking at is not the real thing!

Trust and integrity are vitally important when marketing what may be the most important purchase of their customers’ lives, so professionals in this space must always prioritize ethics, transparency and accountability.

The Role Of Real Estate Professionals In An AI-Driven World

With generative AI increasingly handling routine and analytics-based tasks, real estate agents, appraisers, brokers and marketers will find their focus shifting towards higher-value, strategic responsibilities.

Professionals who prioritize developing human-to-human skills such as communication, customer-centric problem-solving and relationship-building will find they are more in demand than ever.

So too will those who develop an aptitude for leveraging and working alongside AI tools in order to become more efficient at day-to-day aspects of their work.

As in other professions, while some jobs may be lost – entry-level customer service roles, for example, are predicted to be at particular risk – new ones are likely to be created. These are might include prompt engineers who can configure generative AI tools to do the required work, and technology integrators who will identify use cases and procure solutions.

The fact remains, however, that real estate industry is highly competition-driven. Career progression is frequently determined by the ability to generate sales and close deals more effectively than competitors.

It’s this reason, above all else, that means generative AI will quickly become an important tool in the professional toolbox, and those that learn to adapt and leverage them are likely to emerge as winners.

Scientists have developed nanobots — tiny robots at nanoscale — that can enter our bloodstream and even bypass the blood-brain barrier.

This technology has enormous potential benefits for things like taking samples, collecting and transmitting data, and drug delivery — but the potential for abuse is also high. In the future, nanobots may even be used to transmit human thought.

Weaponized nanobots could kill a specific person or group of people, or even rewrite their memories so they turn against their own side. There are also serious privacy concerns in our modern world of highly-connected devices. What protects our medical data and our thoughts, in the world of nanobots? Strong regulation and oversight are necessary to provide transparency and prevent these

While there are a number of beneficial uses for deepfake technology — like recreating historical figures for educational environments or bringing AI-enabled, synthetic media accessibility tools to people who need them — malicious use of this technology is a concern.

Deepfakes can be used to create images and videos of anyone, including celebrities, politicians, or technology leaders, and could be used to support any agenda. Deepfakes have gotten so good that it is hard to tell the difference between real footage and digital fakes.

And as we enter the metaverse and spend more time in the virtual world, we’ll need ways to verify our identity so our interactions with others are protected and safe.

In our increasingly digitized world, we can track nearly everything. Companies are tracking workers’ keystrokes, and police departments are using facial recognition to monitor people’s actions and movements.

This type of digital surveillance poses a threat to human rights, and opens the door to enormous potential abuse.

The United Nations (UN) has publicly condemned arbitrary and unlawful digital surveillance as an infringement on human rights. David Kaye, the UN Special Rapporteur on Freedom of Opinion and Expression, called for a moratorium on the global sales and transfer of digital surveillance tools until we can put legal policies in place to hold organizations and governments accountable for how these tools are being used.