Tag Archives: general
#433301 ‘Happiness Tech’ Is On the Rise. Is ...
We often get so fixated on technological progress that we forget it’s merely one component of the entirety of human progress. Technological advancement does not necessarily correlate with increases in human mental well-being.
While cleaner energy, access to education, and higher employment rates can improve quality of life, they do not guarantee happiness and inner peace. Amid what appears to be an increasing abundance of resources and ongoing human progress, we are experiencing a mental health epidemic, with high anxiety and depression rates. This is especially true in the developed world, where we have access to luxuries our ancestors couldn’t even dream of—all the world’s information contained in a device we hold in the palm of our hands, for example.
But as you may have realized through your own experience, technology can make us feel worse instead of better. Social media can become a tool for comparison and a source of debilitating status anxiety. Increased access to goods and services, along with the rise of consumerism, can lead people to choose “stuff” over true sources of meaning and get trapped in a hedonistic treadmill of materialism. Tools like artificial intelligence and big data could lead to violation of our privacy and autonomy. The digital world can take us away from the beauty of the present moment.
Understanding Happiness
How we use technology can significantly impact our happiness. In this context, “happiness” refers to a general sense of well-being, gratitude, and inner peace. Even with such a simple definition, it is a state of mind many people will admit they lack.
Eastern philosophies have told us for thousands of years that the problem of human suffering begins with our thoughts and perceptions of the circumstances we are in, as opposed to beginning with the circumstances themselves. As Derren Brown brilliantly points out in Happy: Why More or Less Everything Is Absolutely Fine, “The problem with the modern conception of happiness is that it is seen as some kind of commodity. There is this fantasy that simply by believing in yourself and setting goals you can have anything. But that simply isn’t how life works. The ancients had a much better view of it. They offered an approach of not trying to control things you can’t control, and of lessening your desires and your expectations so you achieve a harmony between what you desire and what you have.”
A core part of feeling more happy is about re-wiring our minds to adjust our expectations, exercise gratitude, escape negative narratives, and live in the present moment.
But can technology help us do that?
Applications for Mental Well-Being
Many doers are asking themselves how they can leverage digital tools to contribute to human happiness.
Meditation and mindfulness are examples of practices we can use to escape the often overwhelming burden of our thoughts and ground our minds into the present. They have become increasingly democratized with the rise of meditation mobile apps, such as Headspace, Gaia, and Calm, that allow millions of people globally to use their phones to learn from experts at a very low cost.
These companies have also partnered with hospitals, airlines, athletic teams, and others that could benefit from increased access to mindfulness and meditation. The popularity of these apps continues to rise as more people recognize their necessity. The combination of mass technology and ancient wisdom is one that can lead to a transformation of the collective consciousness.
Sometimes merely reflecting on the sources of joy in our lives and practicing gratitude can contribute to better well-being. Apps such as Happier encourage users to reflect upon and share pleasant everyday moments in their daily lives. Such exercises are based on the understanding that being happy is a “skill” one can build though practice and through scientifically-proven activities, such as writing down a nice thought and sharing your positivity with the world. Many other tools such as Track Your Happiness and Happstr allow users to track their happiness, which often serves as a valuable source of data to researchers.
There is also a growing body of knowledge that tells us we can achieve happiness by helping others. This “helper’s high” is a result of our brains producing endorphins after having a positive impact on the lives of others. In many shapes and forms, technology has made it easier now more than ever to help other people no matter where they are located. From charitable donations to the rise of social impact organizations, there is an abundance of projects that leverage technology to positively impact individual lives. Platforms like GoVolunteer connect nonprofits with individuals from a variety of skill sets who are looking to gift their abilities to those in need. Kiva allows for fundraising loans that can change lives. These are just a handful of examples of a much wider positive paradigm shift.
The Future of Technology for Well-Being
There is no denying that increasingly powerful and immersive technology can be used to better or worsen the human condition. Today’s leaders will not only have to focus on their ability to use technology to solve a problem or generate greater revenue; they will have to ask themselves if their tech solutions are beneficial or detrimental to human well-being. They will also have to remember that more powerful technology does not always translate to happier users. It is also crucial that future generations be equipped with the values required to use increasingly powerful tools responsibly and ethically.
In the Education 2030 report, the Millennium Project envisions a world wherein portable intelligent devices combined with integrated systems for lifelong learning contribute to better well-being. In this vision, “continuous evaluation of individual learning processes designed to prevent people from growing unstable and/or becoming mentally ill, along with programs aimed at eliminating prejudice and hate, could bring about a more beautiful, loving world.”
There is exciting potential for technology to be leveraged to contribute to human happiness at a massive scale. Yet, technology shouldn’t consume every aspect of our lives, since a life worth living is often about balance. Sometimes, even if just for a few moments, what would make us feel happier is we disconnected from technology to begin with.
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#433284 Tech Can Sustainably Feed Developing ...
In the next 30 years, virtually all net population growth will occur in urban regions of developing countries. At the same time, worldwide food production will become increasingly limited by the availability of land, water, and energy. These constraints will be further worsened by climate change and the expected addition of two billion people to today’s four billion now living in urban regions. Meanwhile, current urban food ecosystems in the developing world are inefficient and critically inadequate to meet the challenges of the future.
Combined, these trends could have catastrophic economic and political consequences. A new path forward for urban food ecosystems needs to be found. But what is that path?
New technologies, coupled with new business models and supportive government policies, can create more resilient urban food ecosystems in the coming decades. These tech-enabled systems can sustainably link rural, peri-urban (areas just outside cities), and urban producers and consumers, increase overall food production, and generate opportunities for new businesses and jobs (Figure 1).
Figure 1: The urban food value chain nodes from rural, peri-urban and urban producers
to servicing end customers in urban and peri-urban markets.
Here’s a glimpse of the changes technology may bring to the systems feeding cities in the future.
A technology-linked urban food ecosystem would create unprecedented opportunities for small farms to reach wider markets and progress from subsistence farming to commercially producing niche cash crops and animal protein, such as poultry, fish, pork, and insects.
Meanwhile, new opportunities within cities will appear with the creation of vertical farms and other controlled-environment agricultural systems as well as production of plant-based and 3D printed foods and cultured meat. Uberized facilitation of production and distribution of food will reduce bottlenecks and provide new business opportunities and jobs. Off-the-shelf precision agriculture technology will increasingly be the new norm, from smallholders to larger producers.
As part of Agricultural Revolution 4.0, all this will be integrated into the larger collaborative economy—connected by digital platforms, the cloud, and the Internet of Things and powered by artificial intelligence. It will more efficiently and effectively use resources and people to connect the nexus of food, water, energy, nutrition, and human health. It will also aid in the development of a circular economy that is designed to be restorative and regenerative, minimizing waste and maximizing recycling and reuse to build economic, natural, and social capital.
In short, technology will enable transformation of urban food ecosystems, from expanded production in cities to more efficient and inclusive distribution and closer connections with rural farmers. Here’s a closer look at seven tech-driven trends that will help feed tomorrow’s cities.
1. Worldwide Connectivity: Information, Learning, and Markets
Connectivity from simple cell phone SMS communication to internet-enabled smartphones and cloud services are providing platforms for the increasingly powerful technologies enabling development of a new agricultural revolution. Internet connections currently reach more than 4 billion people, about 55% of the global population. That number will grow fast in coming years.
These information and communications technologies connect food producers to consumers with just-in-time data, enhanced good agricultural practices, mobile money and credit, telecommunications, market information and merchandising, and greater transparency and traceability of goods and services throughout the value chain. Text messages on mobile devices have become the one-stop-shop for small farmers to place orders, gain technology information for best management practices, and access market information to increase profitability.
Hershey’s CocoaLink in Ghana, for example, uses text and voice messages with cocoa industry experts and small farm producers. Digital Green is a technology-enabled communication system in Asia and Africa to bring needed agricultural and management practices to small farmers in their own language by filming and recording successful farmers in their own communities. MFarm is a mobile app that connects Kenyan farmers with urban markets via text messaging.
2. Blockchain Technology: Greater Access to Basic Financial Services and Enhanced Food Safety
Gaining access to credit and executing financial transactions have been persistent constraints for small farm producers. Blockchain promises to help the unbanked access basic financial services.
The Gates Foundation has released an open source platform, Mojaloop, to allow software developers and banks and financial service providers to build secure digital payment platforms at scale. Mojaloop software uses more secure blockchain technology to enable urban food system players in the developing world to conduct business and trade. The free software reduces complexity and cost in building payment platforms to connect small farmers with customers, merchants, banks, and mobile money providers. Such digital financial services will allow small farm producers in the developing world to conduct business without a brick-and-mortar bank.
Blockchain is also important for traceability and transparency requirements to meet food regulatory and consumer requirement during the production, post-harvest, shipping, processing and distribution to consumers. Combining blockchain with RFID technologies also will enhance food safety.
3. Uberized Services: On-Demand Equipment, Storage, and More
Uberized services can advance development of the urban food ecosystem across the spectrum, from rural to peri-urban to urban food production and distribution. Whereas Uber and Airbnb enable sharing of rides and homes, the model can be extended in the developing world to include on-demand use of expensive equipment, such as farm machinery, or storage space.
This includes uberization of planting and harvesting equipment (Hello Tractor), transportation vehicles, refrigeration facilities for temporary storage of perishable product, and “cloud kitchens” (EasyAppetite in Nigeria, FoodCourt in Rwanda, and Swiggy and Zomto in India) that produce fresh meals to be delivered to urban customers, enabling young people with motorbikes and cell phones to become entrepreneurs or contractors delivering meals to urban customers.
Another uberized service is marketing and distributing “ugly food” or imperfect produce to reduce food waste. About a third of the world’s food goes to waste, often because of appearance; this is enough to feed two billion people. Such services supply consumers with cheaper, nutritious, tasty, healthy fruits and vegetables that would normally be discarded as culls due to imperfections in shape or size.
4. Technology for Producing Plant-Based Foods in Cities
We need to change diet choices through education and marketing and by developing tasty plant-based substitutes. This is not only critical for environmental sustainability, but also offers opportunities for new businesses and services. It turns out that current agricultural production systems for “red meat” have a far greater detrimental impact on the environment than automobiles.
There have been great advances in plant-based foods, like the Impossible Burger and Beyond Meat, that can satisfy the consumer’s experience and perception of meat. Rather than giving up the experience of eating red meat, technology is enabling marketable, attractive plant-based products that can potentially drastically reduce world per capita consumption of red meat.
5. Cellular Agriculture, Lab-Grown Meat, and 3D Printed Food
Lab-grown meat, literally meat grown from cultured cells, may radically change where and how protein and food is produced, including the cities where it is consumed. There is a wide range of innovative alternatives to traditional meats that can supplement the need for livestock, farms, and butchers. The history of innovation is about getting rid of the bottleneck in the system, and with meat, the bottleneck is the animal. Finless Foods is a new company trying to replicate fish fillets, for example, while Memphis meats is working on beef and poultry.
3D printing or additive manufacturing is a “general purpose technology” used for making, plastic toys, human tissues, aircraft parts, and buildings. 3D printing can also be used to convert alternative ingredients such as proteins from algae, beet leaves, or insects into tasty and healthy products that can be produced by small, inexpensive printers in home kitchens. The food can be customized for individual health needs as well as preferences. 3D printing can also contribute to the food ecosystem by making possible on-demand replacement parts—which are badly needed in the developing world for tractors, pumps, and other equipment. Catapult Design 3D prints tractor replacement parts as well as corn shellers, cart designs, prosthetic limbs, and rolling water barrels for the Indian market.
6. Alt Farming: Vertical Farms to Produce Food in Urban Centers
Urban food ecosystem production systems will rely not only on field-grown crops, but also on production of food within cities. There are a host of new, alternative production systems using “controlled environmental agriculture.” These include low-cost, protected poly hoop houses, greenhouses, roof-top and sack/container gardens, and vertical farming in buildings using artificial lighting. Vertical farms enable year-round production of selected crops, regardless of weather—which will be increasingly important in response to climate change—and without concern for deteriorating soil conditions that affect crop quality and productivity. AeroFarms claims 390 times more productivity per square foot than normal field production.
7. Biotechnology and Nanotechnology for Sustainable Intensification of Agriculture
CRISPR is a promising gene editing technology that can be used to enhance crop productivity while avoiding societal concerns about GMOs. CRISPR can accelerate traditional breeding and selection programs for developing new climate and disease-resistant, higher-yielding, nutritious crops and animals.
Plant-derived coating materials, developed with nanotechnology, can decrease waste, extend shelf-life and transportability of fruits and vegetables, and significantly reduce post-harvest crop loss in developing countries that lack adequate refrigeration. Nanotechnology is also used in polymers to coat seeds to increase their shelf-life and increase their germination success and production for niche, high-value crops.
Putting It All Together
The next generation “urban food industry” will be part of the larger collaborative economy that is connected by digital platforms, the cloud, and the Internet of Things. A tech-enabled urban food ecosystem integrated with new business models and smart agricultural policies offers the opportunity for sustainable intensification (doing more with less) of agriculture to feed a rapidly growing global urban population—while also creating viable economic opportunities for rural and peri-urban as well as urban producers and value-chain players.
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#432880 Google’s Duplex Raises the Question: ...
By now, you’ve probably seen Google’s new Duplex software, which promises to call people on your behalf to book appointments for haircuts and the like. As yet, it only exists in demo form, but already it seems like Google has made a big stride towards capturing a market that plenty of companies have had their eye on for quite some time. This software is impressive, but it raises questions.
Many of you will be familiar with the stilted, robotic conversations you can have with early chatbots that are, essentially, glorified menus. Instead of pressing 1 to confirm or 2 to re-enter, some of these bots would allow for simple commands like “Yes” or “No,” replacing the buttons with limited ability to recognize a few words. Using them was often a far more frustrating experience than attempting to use a menu—there are few things more irritating than a robot saying, “Sorry, your response was not recognized.”
Google Duplex scheduling a hair salon appointment:
Google Duplex calling a restaurant:
Even getting the response recognized is hard enough. After all, there are countless different nuances and accents to baffle voice recognition software, and endless turns of phrase that amount to saying the same thing that can confound natural language processing (NLP), especially if you like your phrasing quirky.
You may think that standard customer-service type conversations all travel the same route, using similar words and phrasing. But when there are over 80,000 ways to order coffee, and making a mistake is frowned upon, even simple tasks require high accuracy over a huge dataset.
Advances in audio processing, neural networks, and NLP, as well as raw computing power, have meant that basic recognition of what someone is trying to say is less of an issue. Soundhound’s virtual assistant prides itself on being able to process complicated requests (perhaps needlessly complicated).
The deeper issue, as with all attempts to develop conversational machines, is one of understanding context. There are so many ways a conversation can go that attempting to construct a conversation two or three layers deep quickly runs into problems. Multiply the thousands of things people might say by the thousands they might say next, and the combinatorics of the challenge runs away from most chatbots, leaving them as either glorified menus, gimmicks, or rather bizarre to talk to.
Yet Google, who surely remembers from Glass the risk of premature debuts for technology, especially the kind that ask you to rethink how you interact with or trust in software, must have faith in Duplex to show it on the world stage. We know that startups like Semantic Machines and x.ai have received serious funding to perform very similar functions, using natural-language conversations to perform computing tasks, schedule meetings, book hotels, or purchase items.
It’s no great leap to imagine Google will soon do the same, bringing us closer to a world of onboard computing, where Lens labels the world around us and their assistant arranges it for us (all the while gathering more and more data it can convert into personalized ads). The early demos showed some clever tricks for keeping the conversation within a fairly narrow realm where the AI should be comfortable and competent, and the blog post that accompanied the release shows just how much effort has gone into the technology.
Yet given the privacy and ethics funk the tech industry finds itself in, and people’s general unease about AI, the main reaction to Duplex’s impressive demo was concern. The voice sounded too natural, bringing to mind Lyrebird and their warnings of deepfakes. You might trust “Do the Right Thing” Google with this technology, but it could usher in an era when automated robo-callers are far more convincing.
A more human-like voice may sound like a perfectly innocuous improvement, but the fact that the assistant interjects naturalistic “umm” and “mm-hm” responses to more perfectly mimic a human rubbed a lot of people the wrong way. This wasn’t just a voice assistant trying to sound less grinding and robotic; it was actively trying to deceive people into thinking they were talking to a human.
Google is running the risk of trying to get to conversational AI by going straight through the uncanny valley.
“Google’s experiments do appear to have been designed to deceive,” said Dr. Thomas King of the Oxford Internet Institute’s Digital Ethics Lab, according to Techcrunch. “Their main hypothesis was ‘can you distinguish this from a real person?’ In this case it’s unclear why their hypothesis was about deception and not the user experience… there should be some kind of mechanism there to let people know what it is they are speaking to.”
From Google’s perspective, being able to say “90 percent of callers can’t tell the difference between this and a human personal assistant” is an excellent marketing ploy, even though statistics about how many interactions are successful might be more relevant.
In fact, Duplex runs contrary to pretty much every major recommendation about ethics for the use of robotics or artificial intelligence, not to mention certain eavesdropping laws. Transparency is key to holding machines (and the people who design them) accountable, especially when it comes to decision-making.
Then there are the more subtle social issues. One prominent effect social media has had is to allow people to silo themselves; in echo chambers of like-minded individuals, it’s hard to see how other opinions exist. Technology exacerbates this by removing the evolutionary cues that go along with face-to-face interaction. Confronted with a pair of human eyes, people are more generous. Confronted with a Twitter avatar or a Facebook interface, people hurl abuse and criticism they’d never dream of using in a public setting.
Now that we can use technology to interact with ever fewer people, will it change us? Is it fair to offload the burden of dealing with a robot onto the poor human at the other end of the line, who might have to deal with dozens of such calls a day? Google has said that if the AI is in trouble, it will put you through to a human, which might help save receptionists from the hell of trying to explain a concept to dozens of dumbfounded AI assistants all day. But there’s always the risk that failures will be blamed on the person and not the machine.
As AI advances, could we end up treating the dwindling number of people in these “customer-facing” roles as the buggiest part of a fully automatic service? Will people start accusing each other of being robots on the phone, as well as on Twitter?
Google has provided plenty of reassurances about how the system will be used. They have said they will ensure that the system is identified, and it’s hardly difficult to resolve this problem; a slight change in the script from their demo would do it. For now, consumers will likely appreciate moves that make it clear whether the “intelligent agents” that make major decisions for us, that we interact with daily, and that hide behind social media avatars or phone numbers are real or artificial.
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#432568 Tech Optimists See a Golden ...
Technology evangelists dream about a future where we’re all liberated from the more mundane aspects of our jobs by artificial intelligence. Other futurists go further, imagining AI will enable us to become superhuman, enhancing our intelligence, abandoning our mortal bodies, and uploading ourselves to the cloud.
Paradise is all very well, although your mileage may vary on whether these scenarios are realistic or desirable. The real question is, how do we get there?
Economist John Maynard Keynes notably argued in favor of active intervention when an economic crisis hits, rather than waiting for the markets to settle down to a more healthy equilibrium in the long run. His rebuttal to critics was, “In the long run, we are all dead.” After all, if it takes 50 years of upheaval and economic chaos for things to return to normality, there has been an immense amount of human suffering first.
Similar problems arise with the transition to a world where AI is intimately involved in our lives. In the long term, automation of labor might benefit the human species immensely. But in the short term, it has all kinds of potential pitfalls, especially in exacerbating inequality within societies where AI takes on a larger role. A new report from the Institute for Public Policy Research has deep concerns about the future of work.
Uneven Distribution
While the report doesn’t foresee the same gloom and doom of mass unemployment that other commentators have considered, the concern is that the gains in productivity and economic benefits from AI will be unevenly distributed. In the UK, jobs that account for £290 billion worth of wages in today’s economy could potentially be automated with current technology. But these are disproportionately jobs held by people who are already suffering from social inequality.
Low-wage jobs are five times more likely to be automated than high-wage jobs. A greater proportion of jobs held by women are likely to be automated. The solution that’s often suggested is that people should simply “retrain”; but if no funding or assistance is provided, this burden is too much to bear. You can’t expect people to seamlessly transition from driving taxis to writing self-driving car software without help. As we have already seen, inequality is exacerbated when jobs that don’t require advanced education (even if they require a great deal of technical skill) are the first to go.
No Room for Beginners
Optimists say algorithms won’t replace humans, but will instead liberate us from the dull parts of our jobs. Lawyers used to have to spend hours trawling through case law to find legal precedents; now AI can identify the most relevant documents for them. Doctors no longer need to look through endless scans and perform diagnostic tests; machines can do this, leaving the decision-making to humans. This boosts productivity and provides invaluable tools for workers.
But there are issues with this rosy picture. If humans need to do less work, the economic incentive is for the boss to reduce their hours. Some of these “dull, routine” parts of the job were traditionally how people getting into the field learned the ropes: paralegals used to look through case law, but AI may render them obsolete. Even in the field of journalism, there’s now software that will rewrite press releases for publication, traditionally something close to an entry-level task. If there are no entry-level jobs, or if entry-level now requires years of training, the result is to exacerbate inequality and reduce social mobility.
Automating Our Biases
The adoption of algorithms into employment has already had negative impacts on equality. Cathy O’Neil, mathematics PhD from Harvard, raises these concerns in her excellent book Weapons of Math Destruction. She notes that algorithms designed by humans often encode the biases of that society, whether they’re racial or based on gender and sexuality.
Google’s search engine advertises more executive-level jobs to users it thinks are male. AI programs predict that black offenders are more likely to re-offend than white offenders; they receive correspondingly longer sentences. It needn’t necessarily be that bias has been actively programmed; perhaps the algorithms just learn from historical data, but this means they will perpetuate historical inequalities.
Take candidate-screening software HireVue, used by many major corporations to assess new employees. It analyzes “verbal and non-verbal cues” of candidates, comparing them to employees that historically did well. Either way, according to Cathy O’Neil, they are “using people’s fear and trust of mathematics to prevent them from asking questions.” With no transparency or understanding of how the algorithm generates its results, and no consensus over who’s responsible for the results, discrimination can occur automatically, on a massive scale.
Combine this with other demographic trends. In rich countries, people are living longer. An increasing burden will be placed on a shrinking tax base to support that elderly population. A recent study said that due to the accumulation of wealth in older generations, millennials stand to inherit more than any previous generation, but it won’t happen until they’re in their 60s. Meanwhile, those with savings and capital will benefit as the economy shifts: the stock market and GDP will grow, but wages and equality will fall, a situation that favors people who are already wealthy.
Even in the most dramatic AI scenarios, inequality is exacerbated. If someone develops a general intelligence that’s near-human or super-human, and they manage to control and monopolize it, they instantly become immensely wealthy and powerful. If the glorious technological future that Silicon Valley enthusiasts dream about is only going to serve to make the growing gaps wider and strengthen existing unfair power structures, is it something worth striving for?
What Makes a Utopia?
We urgently need to redefine our notion of progress. Philosophers worry about an AI that is misaligned—the things it seeks to maximize are not the things we want maximized. At the same time, we measure the development of our countries by GDP, not the quality of life of workers or the equality of opportunity in the society. Growing wealth with increased inequality is not progress.
Some people will take the position that there are always winners and losers in society, and that any attempt to redress the inequalities of our society will stifle economic growth and leave everyone worse off. Some will see this as an argument for a new economic model, based around universal basic income. Any moves towards this will need to take care that it’s affordable, sustainable, and doesn’t lead towards an entrenched two-tier society.
Walter Schiedel’s book The Great Leveller is a huge survey of inequality across all of human history, from the 21st century to prehistoric cave-dwellers. He argues that only revolutions, wars, and other catastrophes have historically reduced inequality: a perfect example is the Black Death in Europe, which (by reducing the population and therefore the labor supply that was available) increased wages and reduced inequality. Meanwhile, our solution to the financial crisis of 2007-8 may have only made the problem worse.
But in a world of nuclear weapons, of biowarfare, of cyberwarfare—a world of unprecedented, complex, distributed threats—the consequences of these “safety valves” could be worse than ever before. Inequality increases the risk of global catastrophe, and global catastrophes could scupper any progress towards the techno-utopia that the utopians dream of. And a society with entrenched inequality is no utopia at all.
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