This year’s trend is all about hyperautomation,blockchain, Artificial Intelligence security, and everything technology.
The words “Human Augmentation” conjure up notions thatseem out of this world, such as advanced high-technology cyborgs. In reality, however,we have been augmenting parts of the human body for hundreds of years now.Everyday things like eyeglasses, hearing aids, and limb prosthetics justevolved into cochlear implants and wearable technology. Even laser eye surgerythat was considered bizarre has now turned into a conventional option.
With the constant advances and development in thefield of technology, it has now moved on ahead of augmentation that substitutesa human ability and into augmentation that produces superhuman abilities.
So would it be possible for scientists to develop atechnology to advance the brain to boost memory, or implant a chip to decodeneural patterns? Would it be possible that autoworkers would have exoskeletonsas a standard uniform, empowering them to lift weights beyond the average humancapacity? Would it be possible for doctors to implant sensors that can monitorhow drugs move inside a body?
Whether these developments really happen or not willsignificantly influence the world. This makes human augmentation one of the 10strategic technology trends that will make significant opportunities for theupcoming years.
The other trends are focused on how these technologies will transform people and the places that they are in (consumers, employees, homes, businesses, etc.). This is because we believe that in order to further advance technology even further, we have to consider the human side of the world first since at the end of the day, technology is there to make life easier for humans.
- Hyper automation
Automation utilizes technology toautomate responsibilities that normally require humans.
Hyperautomation deals with the use oftechnologies such as machine learning (ML) and artificial intelligence (AI) torapidly and drastically automate processes and augment humans. This extendsover an array of tools that can be automated, but it also applies to therefinement of the automation like discovering, analyzing, designing,automation, measuring, monitoring, and reassessing.
Because of our complexity, no singletool can displace humans. That is why hyperautomation requires an aggregationof tools such as robotic process automation (RPA), intelligent businessmanagement software (iBPMS), and Artificial Intelligence, with the goal ofimproved and advanced AI-driven decision-making capacities.
Hyperautomation also often result inthe creation of a digital twin of the organization which allows organizationsto envision how functions, processes, and key performance indicators combine toaccelerate value. The digital twin organization then becomes an essential partof the automation process as it provides real-time and constant intelligenceabout the organization and valuable business opportunities.
2. Multi experience
Multi experience replaces people thatare great with technology with technology that is greater than people. Theconventional concept of a computer evolves from a singular point of interactionto incorporating multisensory and multi-touchpoint technology like wearablesand high-tech computer sensors.
A great example for this one isDomino’s Pizza’s app-based ordering that involves self-driving pizza deliveryvehicles, a pizza tracker, and smart speaker interfaces.
The multiexperience tech currentlyfocuses on immersive activities that use the combination of augmented, virtual,and mixed reality on top of advanced human-machine interfaces and sensingtechnologies.
Democratization of technology impliesgiving people easier access to technical or business expertise withoutextensive and expensive preparation. The four main focuses are on the areas ofapplication development, data and analytics, design, and knowledge, oftendubbed as “citizen access.” The rise in democratization has contributed to therise of citizen data scientists, citizen programmers, and a lot more.
This technology enabled developers toproduce data models without requiring the skills of a data scientist. Theycould easily make models by using AI-driven development that could generatecode and automate testing.
4. Human augmentation
As briefly discussed above, humanaugmentation is the use of technology to improve a person’s cognitive andphysical senses.
Physical augmentation develops anintegral physical ability by implanting or hosting a technology inside or onthe human body.
The automotive and mining industriesuse wearables to improve worker safety while industries like the retail andtravel industry use wearables to boost productivity.
Physical augmentation has four main categories.
- Sensory augmentation like hearing aids, Lasik, andeyeglasses.
- Appendage and physiological function augmentation likeexoskeletons and prosthetics.
- Brain augmentation like neural implants to treat seizures.
- Genetic augmentation like cell and gene therapy.
Artificial Intelligence and MachineLearning are now being frequently used to create decisions instead of humans.
Cognitive augmentation heightens ahuman’s ability to think and execute better choices like utilizing informationand applications to sharpen learning or new experiences. Cognitive augmentationalso incorporates some technology in the brain augmentation category asphysical implants that deal with cognitive thought.
However, human augmentation brings aseries of cultural and ethical implications making it a little more complicatedthan the rest of the technological trends enumerated in this list.
5. Transparencyand traceability
The development of technology isbuilding a trust crisis. As users become more conscious of how their data isbeing gathered and managed, businesses are also realizing the risingaccountability of collecting and gathering data.
Furthermore, since ArtificialIntelligence and Machine Learning are also being used more often to settledecisions instead of humans, trust crisis is growing and driving the necessityfor designs like understandable AI and AI governance.
Transparency and traceability, therefore, require a focus on six key factors of trust: Ethics, integrity, accountability, competence, openness, and consistency.
6. Theempowered edge
Edge computing is a topology wherecontent collection and information processing and delivery are set closer tothe sources of the information. The main concept behind this is that havinglocal traffic and distribution will minimize latency. This includes all thetechnology on the Internet of Things (IoT). The empowered edge studies howdevices are growing and developing frameworks for smart spaces and promptspivotal applications and services closer to the consumers and devices that utilizethem.
By the year 2023, it’s possible that we’ll have 20 times as many smart devices at the edge of the network as in traditional IT roles.
Autonomous devices including drones,robots, and appliances employ AI to complete duties normally done by humans.This technology functions by using intelligence from semiautonomous tocompletely autonomous under a variety of conditions in air, sea, and land.
As of now, autonomous devices aremainly used in controlled environments like a mine or a warehouse, but expertsestimate that they will eventually be utilized in public areas. Autonomousdevices will also shift from stand-alone to collaborative groups, similar tothe show-stopping drones used during the 2018 Winter Olympic Games.
Now, autonomous devices cannot displace the human brain and would be most effective with a well-defined, well-scoped purpose.
8. The distributed cloud
The distributed cloud pertains to thedistribution of open cloud services to areas outside the cloud provider’sphysical data hubs but are still regulated by the provider. The cloud provideris liable for all features of cloud service design, delivery, performance,restrictions, and updates. The evolution from a centralized public cloud to adistributed public cloud paves the way for a new period of cloud computing.
Distributed cloud enables data hubs to be established anywhere, solving both technical problems like latency as well as regulatory issues like data independence. Additionally, it offers the advantages of a public cloud service together with the advantages of a private and local cloud.
9. Practical blockchain
Blockchain is an example of adistributed ledger or an expanding chronologically arranged list ofcryptographically signed, permanent transactional records used by all membersin a network.
This enables parties to trace assetsand their origin, a feature that’s useful for traditional assets, but alsoopens the possibilities for other functions including tracing the originalsupplier of a food-borne illness.
Blockchain also allows unfamiliarparties to securely connect in a digital setting and transfer value withoutrequiring a centralized authority.
The blockchain model has five elements:
- A shared and distributed ledger.
- Permanent and traceable ledger.
- Distributed public agreement device.
Unfortunately, blockchain is stillconsidered juvenile for business use because of outstanding technical problemslike poor scalability and interoperability. On a brighter note, blockchain isforeseen to be fully scalable by 2023.
For now, enterprise blockchainspractice a pragmatic approach and execute select elements of a completeblockchain. Everyone with the granted access can see the same information, andintegration is made simple by using a single shared blockchain whiletraditional private models are used for consensus.
With complementary technologies suchas AI and the IoT (Internet of Things), true blockchain or “blockchaincomplete” can potentially transform industries, and eventually, the world’seconomy. This opens the kinds of organizations that could include machines,from money to real estate.
Something as crazy as a car being capable of negotiating insurance prices directly with an insurance company using the data it gathered from its sensors can be possible.
10. AI security
Hyperautomation and autonomousdevices offer vast business opportunities. However, they also open uniquesecurity vulnerabilities and brand-new potential points of attack. So, securityteams must be strengthened to approach such attacks and be ready for the impactthat AI will create on the security space.
Here are three key factors in AIsecurity:
- AI-powered systems protection. This involves securing AI training data,training pipelines, and ML models.
- Enhance security defense. Using machinelearning to follow patterns, uncover breaches, and automate parts of thecybersecurity model.
- Anticipating malicioususe of AI. Being able to identify attacks and being ready to defend againstthem.